Fusion genes associated with progressive prostate cancer

ABSTRACT

The present invention relates to methods and compositions for determining whether a subject having prostate cancer is at greater risk of developing progressive disease, and methods of treating the subjects. It is based, at least in part, on the discovery that approximately 90% of men carrying at least one of the following fusion genes: TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67 and CCNH-05orf30 experienced prostate cancer recurrence, metastases and/or prostate cancer-specific death after radical prostatectomy (each examples of “progressive prostate cancer”), while these outcomes occurred in only 36% of men not carrying any of these fusion genes. It is also based, at least in part, on the discovery that no patient studied survived five years without recurrence if their primary prostate cancer contained a TRMT11-GRIK2 or MTOR-TP53BP1 fusion gene. It is also based, at least in part, on the discovery that the protein encoded by the MAN2A1-FER fusion gene exhibits kinase activity.

PRIORITY CLAIM

This application is a continuation of U.S. patent application Ser. No.15/199,056, filed Jun. 30, 2016, which is a continuation ofInternational Patent Application No. PCT/US2014/072268, filed Dec. 23,2014, which claims priority to U.S. Provisional Patent Application Ser.No. 61/921,836, filed Dec. 30, 2013, U.S. Provisional Patent ApplicationSer. No. 62/014,487, filed Jun. 19, 2014, and U.S. Provisional PatentApplication Ser. No. 62/025,923, filed Jul. 17, 2014, which areincorporated by reference herein in their entireties.

GRANT INFORMATION

This invention was made with government support under Grant Nos. RO1CA098249 and awarded by the National Cancer Institute of the NationalInstitutes of Health. The government has certain rights in theinvention.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has beensubmitted electronically in ASCII format and is hereby incorporated byreference in its entirety. Said ASCII copy, created on Feb. 13, 2018, isnamed 072396_0705_SL.txt and is 19,395 bytes in size.

1. INTRODUCTION

The present invention relates to methods of determining which prostatecancer patients are more likely to develop progressive disease based onthe presence of specific fusion genes, and methods of treating suchpatients.

2. BACKGROUND OF THE INVENTION

Despite a high incidence, only a fraction of men diagnosed with prostatecancer develop metastases and even fewer die from the disease. Themajority of prostate cancers remain asymptomatic and clinicallyindolent. The precise mechanisms for the development of progressive,clinically concerning prostate cancer remain elusive. Furthermore, theinability to predict prostate cancer's potential aggressiveness hasresulted in significant overtreatment of the disease. The dichotomousnature of prostate cancer—a subset of life-threatening malignancies inthe larger background of histological alterations lacking the clinicalfeatures implicit with that label—is a fundamental challenge in diseasemanagement. Therefore, there is a need in the art for methods ofdetermining whether a subject is at an increased risk of developingprogressive prostate cancer.

3. SUMMARY OF THE INVENTION

The present invention relates to methods and compositions fordetermining whether a subject having prostate cancer is at increasedrisk of developing progressive disease, and methods of treating suchsubjects. It is based, at least in part, on the discovery thatapproximately 90% of men carrying at least one of the following fusiongenes: TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017,TMEM135-CCDC67 and CCNH-C5orf30 experienced prostate cancer recurrence,metastases and/or prostate cancer-specific death after radicalprostatectomy (each example of “progressive prostate cancer”), whilethese outcomes occurred in only 36% of men not carrying any of thesefusion genes. It is also based, at least in part, on the discovery thatno patient studied survived five years without recurrence if theirprimary prostate cancer contained a TRMT11-GRIK2 or MTOR-TP53BP1 fusiongene. It is also based, at least in part, on the discovery that theprotein encoded by the MAN2A1-FER fusion gene exhibits kinase activity.

In various non-limiting embodiments, the present invention provides formethods and compositions for identifying fusion genes in a subject,which are indicative that a subject is at increased or even high risk ofmanifesting progressive prostate cancer. Such fusion genes includeTRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017,TMEM135-CCDC67, KDM4B-AC011523.2, MAN2A1-FER, PTEN-NOLC1, CCNH-C5orf30,ZMPSTE24-ZMYM4, CLTC-ETV1, ACPP-SEC13, DOCK7-OLR1 and PCMTD1-SNTG1.Further, based on the presence of specific fusion genes, the presentinvention provides a means for identifying subjects at increased riskfor relapse and/or rapid relapse. In certain non-limiting embodiments,the present invention further provides for methods of treating a subjectat increased risk of manifesting progressive prostate cancer, relapseand/or rapid relapse.

4. BRIEF DESCRIPTION OF THE FIGURES

FIG. 1. Unique fusion gene events. Left panel: Miniature diagrams ofgenome of the fusion genes, the transcription directions, the distancesbetween the joining genes and directions of the fusions. Middle panel:Representative sequencing chromograms of fusion genes. The joining genesequences were indicated (SEQ ID NOs: 45-52). Right panel: Diagrams oftranslation products of fusion genes. Blue-driver gene translationproduct; Red-passenger gene translation product; Orange-noveltranslation products due to frameshift or translation products from anon-gene region.

FIG. 2A-H. Fluorescence in situ hybridization suggests genomerecombination in prostate cancer cells. (A) Schematic diagram of MAN2A1and FER genome recombination and FISH probe positions. RepresentativeFISH images were shown for normal prostate epithelial cells and cancercells positive for MAN2A1-FER fusion. Orange denotes probe 1; Greendenotes probe 2. (B) Schematic diagram of SLC45A2 and AMACR genomerecombination and FISH probe positions. Representative FISH images wereshown for normal prostate epithelial cells and cancer cells positive forSLC45A2-AMACR fusion. Orange denotes probe 1; Green denotes probe 2. (C)Schematic diagram of MTOR and TP53BP1 genome recombination and FISHprobe positions. Representative FISH images were shown for normalprostate epithelial cells and cancer cells positive for MTOR-TP53BP1fusion. Orange denotes probe 1; Green denotes probe 2. (D) Schematicdiagram of TRMT11 and GRIK2 genome recombination and FISH probepositions. Representative FISH images were shown for normal prostateepithelial cells and cancer cells positive for TRMT11-GRIK2 fusion.Orange denotes probe 1; Green denotes probe 2. (E) Schematic diagram ofLRRC59 and FLJ60017 genome recombination and FISH probe positions.Representative FISH images were shown for normal prostate epithelialcells and cancer cells positive for LRRC59-FLJ60017 fusion. Orangedenotes probe 1; Green denotes probe 2. (F) Schematic diagram of TMEM135and CCDC67 genome recombination and FISH probe positions. RepresentativeFISH images were shown for normal prostate epithelial cells and cancercells positive for TMEM135-CCDC67 fusion. Orange denotes probe 1; Greendenotes probe 2. (G) Schematic diagram of CCNH and C5orf30 genomerecombination and FISH probe positions. Representative FISH images wereshown for normal prostate epithelial cells and cancer cells positive forCCNH-C5orf30 fusion. Orange denotes probe 1; Green denotes probe 2. (H)Schematic diagram of KDM4B and AC011523.2 genome recombination and FISHprobe positions. Representative FISH images were shown for normalprostate epithelial cells and cancer cells positive for KDM4B-AC011523.2fusion. Orange denotes probe 1; Green denotes probe 2.

FIG. 3A-D. Fusion genes in prostate cancer are associated withaggressive prostate cancers. (A) Distribution of 8 prostate cancersamples positive for fusion genes. Samples from patients who experiencedrecurrence were indicated with grey (PSADT≥15 months) or dark grey(PSADT<4 months), samples from patients who have no recurrence at least5 years with green, and samples from patients whose clinical follow-upis ongoing but less than 5 years with white (undetermined). (B)Correlation of fusion gene events with prostate cancer recurrence.Percentage of prostate cancer relapse when fusion gene was positive inthe prostate cancer samples was plotted for each fusion gene. Percentageof prostate cancer experiencing recurrence from samples positive forfusion transcripts was plotted for each fusion transcript. Left,University of Pittsburgh Medical Center cohort; Middle, StanfordUniversity Medical Center cohort; Right, University of Wisconsin MadisonMedical Center cohort. (C) ROC analyses of a panel of 8 fusion genespredicting prostate cancer recurrence (top) and short PSADT (bottom).(D) Kaplan-Meier analysis of patients who are positive for any ofTRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017,TMEM135-CCDC67 and CCNH-C5orf30 versus those who are negative for thesefusion events.

FIG. 4A-C. Fusion genes predict recurrence of prostate cancer. (A)Schema of training and validation steps in building fusion geneprediction models for prostate cancer recurrence and short PSADT. Thealgorithm of fusion gene prediction of prostate cancer recurrence andPSADT<4 months was obtained from 90 random-assigned prostate cancersamples from University of Pittsburgh Medical Center (I). The algorithmwas then applied to 89 samples from University of Pittsburgh MedicalCenter (II), 21 samples from Stanford University Medical center (III)and 33 samples from University of Wisconsin Madison Medical Center (IV).(B) Prediction rate of prostate cancer recurrence (top) and PSADT<4months using prostate cancer samples cohorts from University ofPittsburgh Medical Center, Stanford Medical Center, and University ofWisconsin Madison Medical Center, based on algorithm obtained from the90-training sample cohort. (C) Kaplan-Meier analysis of patients whowere positive for any of TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1,LRRC59-FLJ60017, TMEM135-CCDC67 and CCNH-C5orf30 versus those who werenegative for these fusion events. Top, Kaplan-Meier analysis of prostatecancer sample cohort from University of Pittsburgh; P-value is indicatedfor the significant difference in survival between the group that ispositive for at least one fusion transcript and the group that isnegative. Bottom, Kaplan-Meier analysis of prostate cancer sample cohortfrom Stanford University Medical Center; P-value is indicated for thesignificant difference in survival between the group that is positivefor at least one fusion transcript and the group that is negative.

FIG. 5A-B. Combining status of fusion transcript andclinical/pathological parameter to improve prediction of prostate cancerrecurrence. (A) Combining Gleason's grading and the status of 8 fusiontranscripts in prostate cancer samples using LDA technique to predictthe recurrence of prostate cancer. Left, ROC analysis of Gleason aloneor Gleason plus the presence of fusion transcripts using LDA techniquein the prediction of prostate cancer recurrence; P value (permutationtest) is indicated for the significant difference between the ROC curvegenerated by Gleason alone and curve generated by Gleason plus thepresence of fusion transcripts using LDA technique. Middle, Kaplan-Meieranalysis of PSA free survival of prostate cancer patients with Gleason≥8 versus <8 from combined UPMC testing, Wisconsin and Stanford datasets; P-value (Log-rank test) is indicated for the significantdifference in survival between the group that has Gleason score at least8 and the group that has score 7 or less. Right, Kaplan-Meier analysisof PSA free survival of prostate cancer patients with Gleason ≥8 orpositive for any of the 8 fusion transcripts in the prostate cancersamples versus those <8 and negative for fusion transcripts using LDAfrom combined UPMC testing, Wisconsin and Stanford data sets. P-value(Log-rank test) is indicated for the significant difference in survivalbetween the group that is positive for at least one fusion transcript orhas Gleason ≥8 and the group that is negative for fusion transcript andhas Gleason <8. (B) Combining nomogram and the status of 8 fusiontranscripts in prostate cancer samples using LDA technique to predictthe recurrence of prostate cancer. Left, ROC analysis of nomogram aloneor nomogram plus the presence of fusion transcripts using LDA techniquein the prediction of prostate cancer recurrence. P-value (permutationtest) is indicated for the significant difference between the ROC curvegenerated by Nomogram alone and curve generated by Nomogram plus thepresence of fusion transcripts using LDA technique. Middle, Kaplan-Meieranalysis of PSA free survival of prostate cancer patients withprobability >88 versus ≤88 from combined UPMC testing, Wisconsin andStanford data sets; P-value (Log-rank test) is indicated for thesignificant difference in survival between the group that hasprobability >88 PSA free survival and the group that has ≤88probability. Right, Kaplan-Meier analysis of PSA free survival ofprostate cancer patients with Nomogram ≤88 or positive for any of the 8fusion transcripts in the prostate cancer samples versus those >88 andnegative for fusion transcripts using LDA from combined UPMC testing,Wisconsin and Stanford data sets. P-value (Log-rank test) is indicatedfor the significant difference in survival between the group that isnegative for fusion transcript and has probability >88 PSA free survivaland the group that is positive for fusion transcript or has ≤88probability.

FIG. 6. CIRCOS plots of prostate cancer functional genome translocation.Five prostate cancer functional translocations were based on RNAsequencing. Fourteen of these functional translocations were supportedby whole genome sequencing analysis. Functional translocation is definedas at least one transcript identified in the translocation process.Translocations in non-gene area were excluded.

FIG. 7A-B. Identification of fusion genes in 174 prostate samples. (A)RT-PCR of TMEM135-CCDC57, KDM4B-AC011523.2, MAN2A1-FER, TRMT11-GRIK2,CCNH-C5orf30, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ6001, TMPRSS2-ERGwere performed on 213 prostate cancer samples. RT-PCR of β-actin wasused as quality control. The lane assignment is the following:1-TP12-S0943T, 2-TP12-S0916T, 3-TP12-S0967T, 4-TP12-S1059T,5-TP10-S093T, 6-JB770T, 7-TP08PPS0721T, 8-TP10-S0638T, 9-TP12-S1032T,10-TP12-S0624T, 11-TP12-S0981T, 12-TP10PPS0420T, 13-TP12-S0966T,14-TP12-S0988T, 15-TP12-S0704T, 16-PR053T, 17-IB110T, 18-TP12-S0928T,19-TP12-S0816T, 20-TP12-S0789T, 21-TP12-S0805T, 22-TP12-S0803T,23-TP12-S0765T, 24-TP12-S0770T, 25-TP12-S0799T, 26-TP12-S0795T,27-TP12-S0786T, 28-PR534T, 29-TP12-S0790T, 30-TP12-S0740T,31-TP12-S0723T, 32-PR536T, 33-FB76, 34-IB378T, 35-IB180T, 36-HB303T,37-GB368, 38-HB327T, 39-HB346T, 40-PR227T, 41-HB322T, 42-HB658T,43-IB289T, 44-HB492T, 45-IB111T, 46-TP12-S0466T, 47-TP12-S0456T,48-TP12-S0246T, 49-TP12-S0608T, 50-TP12-S0340T, 51-TP12-S0337T,52-TP12-S0048T, 53-TP12-S0191T, 54-TP12-S0194T, 55-TP12-S0049T,56-HB340T, 57-TP12-S0102T, 58-PR530T, 59-1942T, 60-TP12-S1189T,61-13745T, 62-5396T, 63-8432T, 64-HB261T, 65-FB183T, 66-HB591T,67-HB568T, 68-HB526T, 69-TP08-S00542T, 70-IB298T, 71-TP09-S0420T,72-PR303T, 73-GB400T, 74-PR018T, 75-HB603T, 76-PR310T, 77-JB197T,78-PR300T, 79-PR236T, 80-JB154T, 81-PR434T, 82-7504T, 83-25313T,84-8629T, 85-7270T, 86-2671T, 87-4308T, 88-28278T, 89-TP12-S1224T,90-TP12-S0918T, 91-TP12-S1197T, 92-TP12-S0915T, 93-16464T, 94-2644T,95-1199T, 96-15922T, 97-15733T, 98-16947T, 99-19381T, 100-6837T,101-9122T, 102-6647T, 103-4336T, 104-29671T, 105-11462T, 106-8741T,107-IB362T, 108-PR079T, 109-IB483T, 110-IB071T, 111-GB195T, 112-PR521T,113-TP08-500530T, 114-7221T, 115-JB426T, 116-34T, 117-HB951T, 118-FB94T,119-IB273T, 120-DB237T, 121-IB134T, 122-HB021T, 123-HB033T, 124-FB174 T,125-KB170T, 126-FB120T, 127-HB504T, 128-HB305T, 129-FB421T,130-TP09-S0721T, 131-FB238T, 132-HB46T, 133-TP11PP-50638T, 134-PR306T,135-HB207T, 136-HB235T, 137-IB112T, 138-IB136T, 139-PR375T, 140-2HB591T,141-23HB021T, 142-TP09-S0006T, 143-21B483T, 144-2HB568T, 145-M-11462T,146-29825T, 147-3G989122T, 148-1AF8378T, 149-3Q-10614T, 150-4L98-27086T,151-3D994336T, 152-3K5772T, 153-2K98-8378T, 154-14304T, 155-15463T,156-15875T, 157-98TA-83782T, 158-562T, 159-14878T, 160-7943T,161-995772T, 162-678T, 163-9927086T, 164-25265T, 165-HB705T,166-33PR053T, 167-TP12-S0954T, 168-19PR530T, 169-34PR227T, 170-56FB76T,171-TP09-S50704T, 172-78HB340T, 173-23FB120T, 174-23HB346T,175-541B289T, 176-TP13-S0109T, 177-TP13-S0456T, 178-TP13-S0248T,179-TP13-S0464T, 180-TP13-S0043T, 181-TP13-S0314T, 182-8433T,183-863176T, 184-R6TT, 185-84876T, 186-994308T, 187-991199T,188-9812033T, 189-855327T, 190-9814481T, 191-R3T, 192-R13T, 193-R19T,194-84375T, 195-832972T, 196-9210207T, 197-R57T, 198-828142T, 199-R26T,200-23R19T, 201-8713205T, 202-9217293T, 203-R18T, 204-8712362T,205-9412443T, 206-R10T, 207-925R293T, 208-R16T, 209-849731T, 210-67R13T,211-842620T, 212-R59T, 213-SR9R57T. (B) RT-PCR of TMEM135-CCDC67,KDM4B-AC011523.2, MAN2A1-FER, TRMT11-GRIK2, CCNH-C5orf30, SLC45A2-AMACR,MTOR-TP53BP1 and LRRC59-FLJ60017 on 10 organ donor prostate tissues.

FIG. 8. Identification of fusion genes in 30 prostate samples fromStanford University Medical Center. RT-PCR of TMEM135-CCDC67,KDM4B-AC011523.2, MAN2A1-FER, TRMT11-GRIK2, CCNH-C5orf30, SLC45A2-AMACR,MTOR-TP53BP1 and LRRC59-FJL60017 were performed on 30 indicated prostatecancer samples. RT-PCR of β-actin was used as quality control.

FIG. 9. Identification of fusion genes in 36 prostate samples fromUniversity of Wisconsin Madison Medical Center. RT-PCR ofTMEM135-CCDC67, KDM4B-AC011523.2, MAN2A1-FER, TRMT11-GRIK2,CCNH-C5orf30, SLC45A2-AMACR, MTOR-TP53BP1 and LRRC59-FJL60017 wereperformed on 36 indicated prostate cancer samples. RT-PCR of β-actin wasused as quality control.

FIG. 10. Inactivation of GRIK1 and TRMT11 RNA expression in prostatecancer positive for TRMT11-GRIK2 fusion. RT-PCR was performed on RNAfrom TRMT11-GRIK2 fusion gene positive prostate cancer samples usingprimers specific for GRIK2 and TRMT11. Products of RT-PCR using primersspecific for β-actin were used as template normalization control.

FIG. 11. Genome breakpoint analysis of fusion genes. Top panel:Miniature diagrams of genome of the fusion genes, the transcriptiondirections, the distances between the joining genes and directions ofthe chromosome joining. Middle panel: Miniature of fusion genome andtranscription direction. Bottom: Representative sequencing chromogramsencompassing the joining breakpoint of chromosomes (SEQ ID NOs: 53-55).

FIG. 12A-B. Prediction of prostate cancer recurrence and PSADT using apanel of 8 fusion genes. (A) ROC analyses of a panel of 8 fusion genespredicting prostate cancer recurrence using random assigned 90 prostatecancer samples from University of Pittsburgh Medical Center. Dottedline-random prediction; Black line-fusion prediction; Blue dot-optimalprediction. P-value (permutation test) is indicated for the significantdifference between the ROC curve generated by fusion transcripts usingLDA technique and the baseline control curve. (B) ROC analyses of apanel of 8 fusion genes predicting prostate cancer short PSADT (<4months). Dotted line-random prediction; Black line-fusion prediction;Blue dot-optimal prediction. P-value (permutation test) is indicated forthe significant difference between the ROC curve generated by fusiontranscripts using LDA technique and the baseline control curve.

FIG. 13A-C. PTEN-NOLC1 fusion gene in prostate cancer. (A) PTEN-NOLC1fusion transcript. Top panel: Miniature diagrams of genome of the PTENand NOLC1 genes, the transcription direction, the distance between thejoining genes and direction of the fusion. Middle panel: Representativesequencing chromogram of PTEN-NOLC1 transcript. The joining genesequences were indicated (SEQ ID NO: 56). Lower panel: Diagram oftranslation product of fusion transcript. Blue-head gene translationproduct; Red-tail gene translation product. (B) Schematic diagram ofPTEN and NOLC1 genome recombination and FISH probe positions.Representative FISH images were shown for normal prostate epithelialcells and cancer cells positive for TENNOLC1 fusion. Orange (asterisk *)denotes probe 1 (RP11-124B18); Green (plus sign+) denotes probe 2(CTD-3082D22). Fusion joining signals are indicated by green arrows. (C)PTEN-NOLC1 expression in prostate cancer samples. RT-PCRs were performedin 215 samples of prostate cancer using primers specific for PTEN-NOLC1(PN) fusion transcript. RT-PCRs using primers specific for β-actin (BAT)were performed as normalization controls.

FIG. 14. Motif analysis of MAN2A1-FER. Diagram of functional domains ofMAN2A1, FER and MAN2A1-FER fusion proteins.

FIG. 15. Schematic diagram of Genome editing targeting at a fusion genebreakpoint in prostate cancer cells positive for CCNH-C5orf30 (SEQ IDNO: 57).

FIG. 16. Schematic diagram of fusion genes. Left panel: Schematicdiagram of genome of fusion partners. Genetic locus, distance betweenpartners, transcription direction and fusion direction are indicated.Middle panel: Histogram of Sanger sequencing surrounding the fusionpoint of each fusion gene (SEQ ID NOs: 40-44). Right panel: Predictedprotein products of fusion genes. Blue: Head gene protein; Yellow:frameshift translation; Red: tail.

FIG. 17. Schematic diagram of ZMPSTE24-ZMYM5 fusion formation.Functional domains are indicated.

FIG. 18. Schematic diagram of CLTC-ETV1 fusion formation. Functionaldomains are indicated.

FIG. 19. Schematic diagram of ACPP-SEC13 fusion formation. Functionaldomains are indicated.

FIG. 20. Schematic diagram of DOCK7-OLR1 fusion formation. Functionaldomains are indicated.

FIG. 21. Schematic diagram of PCMTD1-SNTG1 fusion formation. Functionaldomains are indicated.

FIG. 22A-F. Pro-growth activity of MAN2A1-FER. (A) Expression ofMAN2A1-FER in primary Prostate cancer Samples Immunoblottings wereperformed using antibodies specific for MAN2A1 (upper panel) or FER(lower panel) on MAN2A1-FER RNA positive (JB770T, FB174T and FB421T) orMAN2A1-FER negative (IB071T, IB136T and HB504T) samples. (B) Expressionof MAN2A1-FER-FLAG in RWPE-1 cells. RWPE-1 cells were transfected withpCDNA4-MAN2A1-FER-FLAG/pCDNA6 vectors. Two stable cell lines (RMF1 andRMF4) were selected to demonstrate tetracycline induced expression ofMAN2A1-FER-FLAG using anti-FLAG antibodies. (C) Expression ofMAN2A1-FER-FLAG accelerates entry to S phase of cell cycle. Cell cyclephases were quantified by flow cytometry analysis of BrdU incorporationand propidium iodine labeling. (D) Co-localization of MAN2A1-FER-FLAGand Golgi resident enzyme N-acetylgalactosaminyltransferase.MAN2A1-FER-FLAG was labeled with FITZ conjugated antibodies specific forFLAG, while N-acetylgalactosaminyltransferase was labeled withRhodamine-conjugated antibodies specific forN-acetylgalactosaminyltransferase. (E) Co-segregation of MAN2A1-FER-FLAGand Nacetylgalactosaminyltranferase in sucrose gradientultra-centrifugation. (F) Expression of MAN2A1-FER-FLAG induced tyrosinephosphorylation of EGFR in the absence of EGFR ligand. RMF1 and RMF4cells were serum starved for 72 hrs, and were subsequently induced withtetracycline (5 μg/ml) for 12 hrs. EGFR was immunoprecipitated withanti-EGFR antibodies, and immunoblotted with anti-phosphotyrosine oranti-pTyr1068 of EGFR or anti-EGFR antibodies.

FIG. 23. Specific killing of MAN2A1-FER expressing cells by Crisotiniband Canertinib. Prostate cancer cell line PC3 was transformed withpCDNA4-MAN2A1-FER-FLAG/pCDNA6. Expression of MAN2A1-FER was induced with5 μg/mL tetracycline. Cells not treated with tetracycline nor any drugwere used as background controls. Upper panel: Crisotinib specificallykills cells expressing MAN2A1-FER. Lower panel: Canertinib specificallykills cells expressing MAN2A1-FER.

FIG. 24. Schematic diagram of SLC45A2-AMACR chimera protein. Fusionbetween SLC45A2 and AMACR results in truncation of two-third of (MFS)domain in SLC45A2, but largely retains CoA-transferase domain of AMACR.

FIG. 25A-I. Pro-growth activity of SLC45A2-AMACR. (A) Expression ofSLC45A2-AMACR in primary Prostate cancer samples Immunoblottings wereperformed using antibodies specific for AMACR (upper panel) or SLC45A2(lower panel) on SLC45A2-AMACR RNA positive (FB174T, HB207T, HB305T andFB238T) or SLC45A2-AMACR negative (6637T, 6647T and 1199T) samples. (B)Expression of SLC45A2-AMACR-FLAG in RWPE-1 cells. RWPE-1 cells weretransfected with pCDNA4-SLC45A2-AMACR-FLAG/pCDNA6 vectors. Two stablecell lines (RSLAM#2 and RSLAM#3) were selected to demonstratetetracycline induced expression of SLC45A2-AMACR-FLAG using anti-FLAGantibodies. (C) SLC45A2-AMACR is primarily located in plasma membraneImmunoblottings were performed on membranous fraction (M) andnon-membranous fraction (NM) of RSLAM#2 cells treated withouttetracycline (upper panel) or with tetracycline (lower panel), usingantibodies specific for AMACR (upper panel) and for FLAG (lower panel).(D) Immunofluorescence staining of AMACR (upper panel) in RSLAM#2 cellstreated without tetracycline using antibodies specific for AMACR or ofSLC45A2-AMACR-FLAG in RSLAM#2 cells treated with tetracycline usingantibodies specific for FLAG. (E) Expression of SLC45A2-AMACR increasescell growth in MTT assays. (F) Expression of SLC45A2-AMACR-FLAGaccelerates entry to S phase of cell cycle. Cell cycle phases werequantified by flowcytometry analysis of BrdU incorporation and propidiumiodine labeling. (G) Expression of SLC45A2-AMACR increases intracellularlevels of PIP2(3,4). (H) Yeast Two-Hybrid validation ofLC45A2-AMACR/SHIP2 interaction. (I) Co-immunoprecipitation of SHIP2 andSLC45A2-AMACR-FLAG in RSLAM#2 cells.

FIG. 26. Ebselen specifically inhibits SLC45A2-AMACR expressing PC3cells. Untransformed RWPE1, NIH3T3 cells and SLC45A2-AMACR transformedPC3 cells treated with (PC3/SLAM tet+) or without tetracycline (PC3/SLAMtet−) were applied with indicated concentration of Ebselen. Cell growthsrelative to unapplied controls were examined. IC50 for PC3/SLAM tet+ is37 μM, while for PC3/SLAM tet− is 173 μM. For NIH3T3 and RWPE1 cells,IC50s are >300 μM.

FIG. 27A-D. PTEN-NOLC1 is localized in the nucleus and promotes cellgrowth. (A) Immunofluorescence staining of PTEN and PTEN-NOLC1-FLAG.NIH3T3 and PC3 cells were transformed with pCDNA4-Pten-NOLC1-FLAG/pCDNA6and induced with tetracycline Immunofluorescence staining were performedusing antibodies specific for FLAG epitope. Uninduced NIH3T3 cells andPC3 cells transfected with pCMV-Pten immunostained with antibodiesspecific for Pten were controls. (B) Cell proliferation induced byPten-NOLC1-FLAG. Cells (2000/well) from (A) were grown for 4 days withtetracycline. Cell numbers were then quantified. Cells not treated withtetracycline were negative controls. (C) Cell cycle analysis of NIH3T3and PC3 cells transformed with pCDNA4-Pten-NOLC1-FLAG/pCDNA6. (D) Colonyformation analysis of NIH3T3 and PC3 cells transformed withpCDNA4-Pten-NOLC1-FLAG/pCDNA6.

FIG. 28A-B. Genetic therapy targeting at TMEM135-CCDC67 genomebreakpoint. (A) Transfection of PC3 cells containing TMEM135-CCDC67breakpoint with pTMEM135-CCDC67-TK-GFP andpNicKase-RFP-gRNA-TMEM135-CCDC67-BrkPt resulted in integration andexpression of TK-GFP. (B) Treatment of ganciclovir of PC3 cells andPC3/TMEM135-CCDC67-BrkPt transfected with pTMEM135-CCDC67-TK-GFP andpNicKase-RFP-gRNA-TMEM135-CCDC67-BrkPt resulted in specific killing ofTMEM135-CCDC67 breakpoint containing PC3 cells.

5. DETAILED DESCRIPTION OF THE INVENTION

For clarity and not by way of limitation the detailed description of theinvention is divided into the following subsections:

(i) fusion genes;

(ii) fusion gene detection;

(iii) diagnostic methods and methods of treatment; and

(vi) kits.

5.1 Fusion Genes

The term “fusion gene,” as used herein, refers to a nucleic acid orprotein sequence which combines elements of the recited genes or theirRNA transcripts in a manner not found in the wild type/normal nucleicacid or protein sequences. For example, but not by way of limitation, ina fusion gene in the form of genomic DNA, the relative positions ofportions of the genomic sequences of the recited genes is alteredrelative to the wild type/normal sequence (for example, as reflected inthe NCBI chromosomal positions or sequences set forth herein). In afusion gene in the form of mRNA, portions of RNA transcripts arisingfrom both component genes are present (not necessarily in the sameregister as the wild-type transcript and possibly including portionsnormally not present in the normal mature transcript). In non-limitingembodiments, such a portion of genomic DNA or mRNA may comprise at leastabout 10 consecutive nucleotides, or at least about 20 consecutivenucleotides, or at least about 30 consecutive nucleotides, or at least40 consecutive nucleotides. In a fusion gene in the form of a protein,portions of amino acid sequences arising from both component genes arepresent (not by way of limitation, at least about 5 consecutive aminoacids or at least about 10 amino acids or at least about 20 amino acidsor at least about 30 amino acids). In this paragraph, portions arisingfrom both genes, transcripts or proteins do not refer to sequences whichmay happen to be identical in the wild type forms of both genes (that isto say, the portions are “unshared”). As such, a fusion gene represents,generally speaking, the splicing together or fusion of genomic elementsnot normally joined together.

The fusion gene TRMT11-GRIK2 is a fusion between the tRNAmethyltransferase 11 homolog (“TRMT11”) and glutamate receptor,ionotropic, kainate 2 (“GRIK2”) genes. The human TRMT11 gene istypically located on chromosome 6q11.1 and the human GRIK2 gene istypically located on chromosome 6q16.3. In certain embodiments, theTRMT11 gene is the human gene having NCBI Gene ID No: 60487, sequencechromosome 6; NC_000006.11 (126307576..126360422) and/or the GRIK2 geneis the human gene having NCBI Gene ID No:2898, sequence chromosome 6;NC_000006.11 (101841584..102517958).

The fusion gene SLC45A2-AMACR is a fusion between the solute carrierfamily 45, member 2 (“SLC45A2”) and alpha-methylacyl-CoA racemase(“AMACR”) genes. The human SLC45A2 gene is typically located on humanchromosome 5p13.2 and the human AMACR gene is typically located onchromosome 5p13. In certain embodiments the SLC45A2 gene is the humangene having NCBI Gene ID No: 51151, sequence chromosome 5; NC_000005.9(33944721..33984780, complement) and/or the AMACR gene is the human genehaving NCBI Gene ID No:23600, sequence chromosome 5; NC_000005.9(33987091..34008220, complement).

The fusion gene MTOR-TP53BP1 is a fusion between the mechanistic targetof rapamycin (“MTOR”) and tumor protein p53 binding protein 1(“TP53BP1”) genes. The human MTOR gene is typically located onchromosome 1p36.2 and the human TP53BP1 gene is typically located onchromosome 15q15-q21. In certain embodiments, the MTOR gene is the humangene having NCBI Gene ID No:2475, sequence chromosome 1 NC_000001.10(11166588..11322614, complement) and/or the TP53BP1 gene is the humangene having NCBI Gene ID No: 7158, sequence chromosome 15; NC_000015.9(43695262..43802707, complement).

The fusion gene LRRC59-FLJ60017 is a fusion between the leucine richrepeat containing 59 (“LRRC59”) gene and the “FLJ60017” nucleic acid.The human LRRC59 gene is typically located on chromosome 17q21.33 andnucleic acid encoding human FLJ60017 is typically located on chromosome11q12.3. In certain embodiments, the LRRC59 gene is the human genehaving NCBI Gene ID No:55379, sequence chromosome 17; NC_000017.10(48458594..48474914, complement) and/or FLJ60017 has a nucleic acidsequence as set forth in GeneBank AK_296299.

The fusion gene TMEM135-CCDC67 is a fusion between the transmembraneprotein 135 (“TMEM135”) and coiled-coil domain containing 67 (“CCDC67”)genes. The human TMEM135 gene is typically located on chromosome 11q14.2and the human CCDC67 gene is typically located on chromosome 11q21. Incertain embodiments the TMEM135 gene is the human gene having NCBI GeneID No: 65084, sequence chromosome 11; NC_000011.9 (86748886..87039876)and/or the CCDC67 gene is the human gene having NCBI Gene ID No: 159989,sequence chromosome 11; NC_000011.9 (93063156..93171636).

The fusion gene CCNH-C5orf30 is a fusion between the cyclin H (“CCNH”)and chromosome 5 open reading frame 30 (“C5orf30”) genes. The human CCNHgene is typically located on chromosome 5q13.3-q14 and the humanC5orf30gene is typically located on chromosome 5q21.1. In certainembodiments, the CCNH gene is the human gene having NCBI Gene ID No:902, sequence chromosome 5; NC_000005.9 (86687310..86708850, complement)and/or the C5orf30gene is the human gene having NCBI Gene ID No: 90355,sequence chromosome 5; NC_000005.9 (102594442..102614361).

The fusion gene KDM4B-AC011523.2 is a fusion between lysine (K)-specificdemethylase 4B (“KDM4B”) and chromosomal region “AC011523.2”. The humanKDM4B gene is typically located on chromosome 19p13.3 and the humanAC011523.2 region is typically located on chromosome 19q13.4. In certainembodiments the KDM4B gene is the human gene having NCBI Gene ID NO:23030, sequence chromosome 19; NC_000019.9 (4969123..5153609); and/orthe AC011523.2 region comprises a sequence as shown in FIG. 1.

The fusion gene MAN2A1-FER is a fusion between mannosidase, alpha, class2A, member 1 (“MAN2A1”) and (fps/fes related) tyrosine kinase (“FER”).The human MAN2A1 gene is typically located on chromosome 5q21.3 and thehuman FER gene is typically located on chromosome 5q21. In certainembodiments, the MAN2A1gene is the human gene having NCBI Gene ID NO:4124, sequence chromosome 5; NC_000005.9 (109025156..109203429) orNC_000005.9 (109034137..109035578); and/or the FER gene is the humangene having NCBI Gene ID NO: 2241, sequence chromosome 5: NC_000005.9(108083523..108523373).

The fusion gene PTEN-NOLC1 is a fusion between the phosphatase andtensin homolog (“PTEN”) and nucleolar and coiled-body phosphoprotein 1(“NOLC1”). The human PTEN gene is typically located on chromosome10q23.3 and the human NOLC1 gene is typically located on chromosome10q24.32. In certain embodiments, the PTEN gene is the human gene havingNCBI Gene ID NO: 5728, sequence chromosome 10; NC_000010.11(87863438..87970345) and/or the NOLC1 gene is the human gene having NCBIGene ID NO: 9221, sequence chromosome 10; NC_000010.11(102152176..102163871).

The fusion gene ZMPSTE24-ZMYM4 is a fusion between zinc metallopeptidaseSTE24 (“ZMPSTE24”) and zinc finger, MYM-type 4 (“ZMYM4”). The humanZMPSTE24 is typically located on chromosome 1p34 and the human ZMYM4gene is typically located on chromosome 1p32-p34. In certainembodiments, the ZMPSTE24 gene is the human gene having NCBI Gene ID NO:10269, sequence chromosome 1; NC_000001.11 (40258050..40294184) and/orthe ZMYM4 gene is the human gene having NCBI Gene ID NO: 9202, sequencechromosome 1; NC_000001.11 (35268850..35421944).

The fusion gene CLTC-ETV1 is a fusion between clathrin, heavy chain (Hc)(“CLTC”) and ets variant 1 (“ETV1”). The human CLTC is typically locatedon chromosome 17q23.1 and the human ETV1 gene is typically located onchromosome 7p21.3. In certain embodiments, the CLTC gene is the humangene having NCBI Gene ID NO: 1213, sequence chromosome 17; NC_000017.11(59619689..59696956) and/or the ETV1gene is the human gene having NCBIGene ID NO: 2115, sequence chromosome 7; NC_000007.14(13891229..13991425, complement).

The fusion gene ACPP-SEC13 is a fusion between acid phosphatase,prostate (“ACPP”) and SEC13 homolog (“SEC13”). The human ACPP istypically located on chromosome 3q22.1 and the human SEC13 gene istypically located on chromosome 3p25-p24. In certain embodiments, theACPP gene is the human gene having NCBI Gene ID NO: 55, sequencechromosome 3; NC_000003.12 (132317367..132368302) and/or the SEC13 geneis the human gene having NCBI Gene ID NO: 6396, sequence chromosome 3;NC_000003.12 (10300929..10321188, complement).

The fusion gene DOCK7-OLR1 is a fusion between dedicator of cytokinesis7 (“DOCK7”) and oxidized low density lipoprotein (lectin-like) receptor1 (“OLR1”). The human DOCK7 is typically located on chromosome 1p31.3and the human OLR1 gene is typically located on chromosome12p13.2-p12.3. In certain embodiments, the DOCK7 gene is the human genehaving NCBI Gene ID NO: 85440, sequence chromosome 1; NC_000001.11(62454726..62688368, complement) and/or the OLR1 gene is the human genehaving NCBI Gene ID NO: 4973, sequence chromosome 12; NC_000012.12(10158300..10172191, complement).

The fusion gene PCMTD1-SNTG1 is a fusion between protein-L-isoaspartate(D-aspartate) O-methyltransferase domain containing 1 (“PCMTD1”) andsyntrophin, gamma 1 (“SNTG1”). The human PCMTD1 is typically located onchromosome 8q11.23 and the human SNTG1 gene is typically located onchromosome 8q11.21. In certain embodiments, the PCMTD1 gene is the humangene having NCBI Gene ID NO: 115294, sequence chromosome 8; NC_000008.11(51817575..51899186, complement) and/or the SNTG1gene is the human genehaving NCBI Gene ID NO: 54212, sequence chromosome 8; NC_000008.11(49909789..50794118).

5.2 Fusion Gene Detection

Any of the foregoing fusion genes described above in section 5.1 may beidentified by methods known in the art. The fusion genes may be detectedby detecting the gene fusion manifested in DNA, RNA or protein. Forexample, and not by way of limitation, the presence of a fusion gene maybe detected by determining the presence of the protein encoded by thefusion gene.

The fusion gene may be detected in a sample of a subject. A “patient” or“subject,” as used interchangeably herein, refers to a human or anon-human subject. Non-limiting examples of non-human subjects includenon-human primates, dogs, cats, mice, etc.

The subject may or may not be previously diagnosed as having prostatecancer.

In certain non-limiting embodiments, a sample includes, but is notlimited to, cells in culture, cell supernatants, cell lysates, serum,blood plasma, biological fluid (e.g., blood, plasma, serum, stool,urine, lymphatic fluid, ascites, ductal lavage, saliva and cerebrospinalfluid) and tissue samples. The source of the sample may be solid tissue(e.g., from a fresh, frozen, and/or preserved organ, tissue sample,biopsy, or aspirate), blood or any blood constituents, bodily fluids(such as, e.g., urine, lymph, cerebral spinal fluid, amniotic fluid,peritoneal fluid or interstitial fluid), or cells from the individual,including circulating cancer cells. In certain non-limiting embodiments,the sample is obtained from a cancer. In certain embodiments, the samplemay be a “biopsy sample” or “clinical sample,” which are samples derivedfrom a subject. In certain embodiments, the sample includes one or moreprostate cancer cells from a subject. In certain embodiments, the one ormore fusion genes can be detected in one or more samples obtained from asubject.

In certain non-limiting embodiments, the fusion gene is detected bynucleic acid hybridization analysis.

In certain non-limiting embodiments, the fusion gene is detected byfluorescent in situ hybridization (FISH) analysis.

In certain non-limiting embodiments, the fusion gene is detected by DNAhybridization, such as, but not limited to, Southern blot analysis.

In certain non-limiting embodiments, the fusion gene is detected by RNAhybridization, such as, but not limited to, Northern blot analysis.

In certain non-limiting embodiments, the fusion gene is detected bynucleic acid sequencing analysis.

In certain non-limiting embodiments, the fusion gene is detected byprobes present on a DNA array, chip or a microarray.

In certain non-limiting embodiments, the fusion gene is detected by amethod comprising Reverse Transcription Polymerase Chain Reaction(“RT-PCR”). In certain embodiments, the fusion gene is detected by amethod comprising RT-PCR using the one or more pairs of primersdisclosed herein (see Table 3).

In certain non-limiting embodiments, the fusion gene is detected byantibody binding analysis such as, but not limited to, Western Blotanalysis and immunohistochemistry.

In certain non-limiting embodiments, where a fusion gene combines genesnot typically present on the same chromosome, FISH analysis maydemonstrate probes binding to the same chromosome. For example, analysismay focus on the chromosome where one gene normally resides and thenhybridization analysis may be performed to determine whether the othergene is present on that chromosome as well.

5.3 Diagnostic Methods and Methods of Treatment

The present invention provides methods for assessing whether a subjecthaving prostate cancer is at increased risk of developing progressivedisease, at an increased risk of relapse and/or at an increased risk ofrapid relapse. The present invention further provides methods oftreating subjects at an increased risk of developing progressivedisease, at an increased risk of relapse and/or at an increased risk ofrapid relapse.

“Increased risk,” as used herein, means at higher risk than subjectslacking one or more of the disclosed fusion genes; in certainnon-limiting embodiments, the risk is increased such that progressiveprostate cancer occurs in more than 50%, more than 60% or more than 70%of individuals bearing said fusion gene in one or more cells of theirprostate cancer.

5.3.1 Diagnostic Methods for Assessing the Risk of Progressive Cancer

The present invention provides for methods of determining whether asubject is at increased risk of manifesting progressive prostate cancer.

In certain non-limiting embodiments, the method of determining whether asubject is at increased risk of manifesting progressive prostate cancercomprises determining whether a sample of the subject contains one ormore fusion genes selected from the group consisting of TRMT11-GRIK2,SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67,KDM4B-AC011523.2, MAN2A1-FER, PTEN-NOLC1, CCNH-C5orf30, ZMPSTE24-ZMYM4,CLTC-ETV1, ACPP-SEC13, DOCK7-OLR1, PCMTD1-SNTG1 or a combinationthereof, where the presence of one or more fusion genes in the sample isindicative that the subject is at increased risk of manifestingprogressive prostate cancer.

In certain embodiments, the method of determining whether a subject isat increased risk of manifesting progressive prostate cancer comprisesdetermining the presence and/or absence of one or more, two or more,three or more, four or more, five or more, six or more, seven or more,eight or more, nine or more, ten or more, eleven or more, twelve ormore, thirteen or more, fourteen or more of the fusion genes disclosedherein in a sample of a subject. In certain embodiments, the sample caninclude one or more prostate cancer cells of a subject.

In certain non-limiting embodiments, the method of determining whether asubject is at increased risk of manifesting progressive prostate cancercomprises determining whether a sample of the subject contains one ormore fusion genes selected from the group consisting of TRMT11-GRIK2,SLC45A2-AMACR, PTEN-NOLC1 or MTOR-TP53BP1, where the presence of one ormore fusion genes in the sample is indicative that the subject is atincreased risk of manifesting progressive prostate cancer.

5.3.2 Diagnostic Methods for Assessing the Risk of Relapse of ProstateCancer

The present invention provides for methods for determining whether asubject is at risk for relapse or rapid relapse of prostate cancer.

In certain non-limiting embodiments, a method of determining whether asubject is at risk for rapid relapse of prostate cancer (as reflected,for example, in a doubling of serum prostate specific antigen (PSA) inless than 4 months), comprises determining the sum of:

{[the vector of whether the fusion gene TMEM135-CCDC67 is present in atumor cell of the subject] times 0.4127877};

plus

{[the vector of whether the fusion gene KDM4B-AC011523.2 is present in atumor cell of the subject] times 0.4091903};

plus

{[the vector of whether the fusion gene MAN2A1-FER is present in a tumorcell of the subject] times 0.3879886};

plus

{[the vector of whether the fusion gene CCNH-C5orf30 is present in atumor cell of the subject] times (−2.0193237)};

plus

{[the vector of whether the fusion gene TRMT11-GRIK2 is present in atumor cell of the subject] times (−2.3301892)};

plus

{[the vector of whether the fusion gene SLC45A2-AMACR is present in atumor cell of the subject] times (−2.1499750)};

plus

{[the vector of whether the fusion gene MTOR-TP53BP1 is present in atumor cell of the subject] times (−2.1140216)};

plus

{[the vector of whether the fusion gene LRRC59-FLJ60017 is present in atumor cell of the subject] times (−0.8611482)};

where if the sum of the above is less than 0.0716, then the subject isat increased risk for exhibiting rapid relapse of prostate cancer. Inthe above, where the particular fusion gene is present, the value of thevector is [+1] and where the particular fusion gene is absent, the valueof the vector is [0].

In certain non-limiting embodiments, a method of determining whether asubject is at risk for relapse of prostate cancer comprises determiningthe sum of:

{[the vector of whether the fusion gene TMEM135-CCDC67 is present in atumor cell of the subject] times (−0.01752496)};

plus

{[the vector of whether the fusion gene KDM4B-AC011523.2 is present in atumor cell of the subject] times (−0.16638222)};

plus

{[the vector of whether the fusion gene MAN2A1-FER is present in a tumorcell of the subject] times 0.67180725};

plus

{[the vector of whether the fusion gene CCNH-C5orf30 is present in atumor cell of the subject] times (−0.62367777)};

plus

{[the vector of whether the fusion gene TRMT11-GRIK2 is present in atumor cell of the subject] times (−2.44068688)};

plus

{[the vector of whether the fusion gene SLC45A2-AMACR is present in atumor cell of the subject] times (−2.18012958)};

plus

{[the vector of whether the fusion gene MTOR-TP53BP1 is present in atumor cell of the subject] times (−1.79668048)};

plus

{[the vector of whether the fusion gene LRRC59-FLJ60017 is present in atumor cell of the subject] times (−1.75487809)};

where if the sum of the above is less than 0.056, then the subject is atincreased risk for exhibiting relapse of prostate cancer. In the above,where the particular fusion gene is present, the value of the vector is[+1] and where the particular fusion gene is absent, the value of thevector is [0].

In certain non-limiting embodiments, the method of determining whether asubject is at increased risk of relapse of prostate cancer comprisesdetermining whether a sample of the subject contains one or more fusiongenes selected from the group consisting of TRMT11-GRIK2, SLC45A2-AMACR,MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67, KDM4B-AC011523.2,MAN2A1-FER, PTEN-NOLC1, CCNH-C5orf30, ZMPSTE24-ZMYM4, CLTC-ETV1,ACPP-SEC13, DOCK7-OLR1, PCMTD1-SNTG1 or a combination thereof, where thepresence of one or more fusion genes in the sample is indicative thatthe subject is at increased risk of relapse, using the followingformula:Z=−0.0325*X+1.6219*Y  [Formula 1]where X % is the Nomogram score of the five-year progression freeprobability after surgery (X can be between 0 and 100) and Y is thepresence of any of the fusion genes (where Y=0 if no fusion genes arepresent, and Y=+1 if one or more fusion genes are present). In theabove, when Z>=−1.9, then the patient is at risk for exhibiting relapseof prostate cancer and when Z<−1.9, then the patient is not at risk forexhibiting relapse of prostate cancer.

5.3.3 Methods of Treatment

The invention further provides methods for treating a subject having anincreased risk for progressive prostate cancer, prostate cancer relapseor prostate cancer rapid relapse.

In certain embodiments, the method of treating a subject comprisesdetermining if the subject is at an increased risk for progressiveprostate cancer by determining the presence of one or more fusion genesselected from the group consisting of TRMT11-GRIK2, SLC45A2-AMACR,MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67, KDM4B-AC011523.2,MAN2A1-FER, PTEN-NOLC1, CCNH-C5orf30, ZMPSTE24-ZMYM4, CLTC-ETV1,ACPP-SEC13, DOCK7-OLR1, PCMTD1-SNTG1 or a combination thereof in asample of the subject, where if one or more fusion genes are present inthe sample so that the subject is at risk then treating the subject toproduce an anti-cancer effect. In certain embodiments, the method caninclude determining the presence or absence of one or more, two or more,three or more, four or more, five or more, six or more, seven or more,eight or more or all nine of the fusion genes disclosed herein.

An “anti-cancer effect” refers to one or more of a reduction inaggregate cancer cell mass, a reduction in cancer cell growth rate, areduction in cancer progression, a reduction in cancer cellproliferation, a reduction in tumor mass, a reduction in tumor volume, areduction in tumor cell proliferation, a reduction in tumor growth rateand/or a reduction in tumor metastasis. In certain embodiments, ananti-cancer effect can refer to a complete response, a partial response,a stable disease (without progression or relapse), a response with alater relapse or progression-free survival in a patient diagnosed withcancer.

In certain embodiments, the method of treating a subject comprisesdetermining if the subject is at an increased risk for progressiveprostate cancer by determining the presence of one or more fusion genesselected from the group consisting TRMT11-GRIK2, SLC45A2-AMACR,PTEN-NOLC1 or MTOR-TP53BP1 or a combination thereof in a sample of thesubject, where if one or more fusion genes are detected in the sample sothat the subject is at risk then treating the subject to produce ananti-cancer effect.

In certain embodiments, the method of treating a subject comprisesdetermining if a patient is at an increased risk for prostate cancerrelapse or rapid relapse as described above in section 5.3, where if thesubject is at increased risk for prostate cancer rapid relapse thentreating the subject to produce an anti-cancer effect in the subject.

In certain embodiments, the method of treating a subject comprisesdetermining if the subject is at an increased risk for progressiveprostate cancer, prostate cancer relapse or rapid relapse as describedabove, where if the subject is at increased risk for progressiveprostate cancer, prostate cancer relapse or rapid relapse, thenadministering to the subject a therapeutically effective amount of aninhibitor. In certain embodiments, the inhibitor can be administered toproduce an anti-cancer effect in a subject.

A “therapeutically effective amount” refers to an amount that is able toachieve one or more of the following: an anti-cancer effect,prolongation of survival and/or prolongation of period until relapse.

In certain embodiments, the method of treating a subject is directed toinhibiting the fusion gene and/or inhibiting the fusion gene product,e.g., the protein and/or RNA encoded by the fusion gene.

Examples of inhibitors include, but are not limited to, compounds,molecules, chemicals, polypeptides and proteins that inhibit and/orreduce the expression and/or activity of the protein encoded by a fusiongene. Alternatively or additionally, the inhibitor can includecompounds, molecules, chemicals, polypeptides and proteins that inhibitand/or reduce the expression and/or activity of one or more downstreamtargets of the fusion gene.

Additional non-limiting examples of inhibitors include ribozymes,antisense oligonucleotides, shRNA molecules and siRNA molecules thatspecifically inhibit or reduce the expression and/or activity of thefusion gene and/or inhibit or reduce the expression and/or activity ofone or more downstream targets of the fusion gene. One non-limitingexample of an inhibitor comprises an antisense, shRNA or siRNA nucleicacid sequence homologous to at least a portion of the fusion genesequence, wherein the homology of the portion relative to the fusiongene sequence is at least about 75 or at least about 80 or at leastabout 85 or at least about 90 or at least about 95 or at least about 98percent, where percent homology can be determined by, for example, BLASTor FASTA software. In certain embodiments, the antisense, the shRNA orsiRNA nucleic acid sequence can be homologous to the sequence at the“junction fragment” that encompasses the boundary between the splicedgenes of the fusion gene. Non-limiting examples of siRNAs homologous tothe junction fragment sequences of the disclosed fusion genes are shownin Table 1.

In certain non-limiting embodiments, the complementary portion mayconstitute at least 10 nucleotides or at least 15 nucleotides or atleast 20 nucleotides or at least 25 nucleotides or at least 30nucleotides and the antisense nucleic acid, shRNA or siRNA molecules maybe up to 15 or up to 20 or up to 25 or up to 30 or up to 35 or up to 40or up to 45 or up to 50 or up to 75 or up to 100 nucleotides in length.Antisense, shRNA or siRNA molecules may comprise DNA or atypical ornon-naturally occurring residues, for example, but not limited to,phosphorothioate residues and locked nucleic acids.

In certain embodiments, an inhibitor can include an antibody, or aderivative thereof, that specifically binds to and inhibits and/orreduces the expression and/or activity of the protein that is encoded bythe fusion gene, e.g., an antagonistic antibody. Alternatively oradditionally, an inhibitor can include an antibody, or derivativethereof, that specifically binds to and inhibits and/or reduces theexpression and/or activity of one or more downstream targets of thefusion gene. The phrase “specifically binds” refers to binding of, forexample, an antibody to an epitope or antigen or antigenic determinantin such a manner that binding can be displaced or competed with a secondpreparation of identical or similar epitope, antigen or antigenicdeterminant. Non-limiting examples of antibodies, and derivativesthereof, that can be used in the disclosed methods include polyclonal ormonoclonal antibodies, chimeric, human, humanized, primatized(CDR-grafted), veneered or single-chain antibodies, phase producedantibodies (e.g., from phage display libraries), as well as functionalbinding fragments of antibodies. Antibody binding fragments, or portionsthereof, include, but are not limited to, Fv, Fab, Fab′ and F(ab′)₂.Such fragments can be produced by enzymatic cleavage or by recombinanttechniques.

In certain embodiments, where the protein encoded by the fusion genedetected in the sample of the subject exhibits kinase activity, themethod of treating a subject can include administering a therapeuticallyeffective amount of an inhibitor to the subject that inhibits and/orreduces the kinase activity of the protein encoded by the fusion gene,i.e., a kinase inhibitor. Non-limiting examples of kinase inhibitorsinclude afatinib, alectinib, axitinib, bevacizumab, bosutinib,cetuximab, crizotinib, dasatinib, erlotinib, fostamatinib, gefitinib,GSK1838705A, ibrutinib, imatinib, lapatinib, lenvatinib, mubritinib,nilotinib, panitumumab, pazopanib, pegaptanib, ranibizumab, ruxolitinib,sorafenib, sunitinib, su6656, trastuzumab, tofacitinib, vandetanib andvemurafenib. For example, and not by way of limitation, if the proteinencoded by the fusion gene detected in a sample of the subject exhibitstyrosine kinase activity, a therapeutically effective amount of atyrosine kinase inhibitor can be administered to the subject.

In certain embodiments, a method of treating a subject can comprisedetermining if the subject is at an increased risk for progressiveprostate cancer by determining the presence of MAN2A1-FER in a sample ofthe subject, where if the MAN2A1-FER fusion gene is present in thesample, then treating the subject with a therapeutically effectiveamount of a FER inhibitor. Non-limiting examples of FER inhibitorsinclude crisotinib, TAE684, WZ-4-49-8 and WZ-4-49-10. In particularnon-limiting embodiments, the FER inhibitor can be derived fromdiaminopyrimidine or pyrazologyrididine compounds.

Further non-limiting examples of FER inhibitors are disclosed in PCTApplication No. WO 2009/019708, the content of which is herebyincorporated by reference in its entirety. In certain embodiments, theFER inhibitor can include tyrosine kinase inhibitors and ALK inhibitorsas FER exhibits high sequence similarity to ALK. In certain embodiments,the FER inhibitor is an antibody that reduces and/or inhibits theexpression and/or activity of the MAN2A1-FER protein. In certainembodiments, the FER inhibitor comprises an siRNA targeting theMAN2A1-FER fusion gene or the juncture sequence of the MAN2A1-FER fusiongene. A non-limiting example of an siRNA sequence targeting theMAN2A1-FER fusion gene is shown in Table 1.

Alternatively or additionally, the method of treating a subjectexpressing the MAN2A1-FER fusion gene can comprise administering to thesubject a compound that reduces and/or inhibits the activity and/orexpression of one or more downstream targets of the MAN2A1-FER fusiongene. For example, and not by way of limitation, the method can includethe inhibition of the EGFR-RAS-BRAF-MEK signaling pathway. Non-limitingexamples of compounds that inhibit EGFR activity include erlotinib,cetuximab, gefitinib, bevacizumab, panitumumab and bortezomib. Anon-limiting example of a compound that inhibits BRAP activity includesRAF265. Non-limiting examples of compounds that inhibits MEK activityincludes binimetinib, vemurafenib, PD-325901, selumetinib andtrametinib. Additional non-limiting examples of compounds that inhibitthe EGFR-RAS-BRAF-MEK signaling pathway include TAK-733, Honokiol,AZD8330, PD318088, BIX 02188, pimasertib, SL-327, BIX 02189, PD98059,MEK162, PD184352 and U0126-EtOH.

In certain embodiments, a method of treating a subject can comprisedetermining if the subject is at an increased risk for progressiveprostate cancer by determining the presence of SLC45A2-AMACR in a sampleof the subject, where if the SLC45A2-AMACR fusion gene is present in thesample, then treating the subject with a therapeutically effectiveamount of a racemase inhibitor and/or an AMACR inhibitor. A non-limitingexample of a racemase and/or AMACR inhibitors includes ebselen,2-(2,5-dihydroxy-4-methylphenyl)-5-methyl benzene-1.4-diol (DMPMB),2-methylsulfanyl-7,9-dihydro-3H-purine-6,8-dithione (MSDTP),2,5-di(pyrazol-1-yl)benzene-1,4-diol (DPZBD), Rose Bengal, Congo Red,3,5-di(pyridin-4-yl)-1,2,4-thiadiazole (DPTD), ebselen oxide and3,7,12-trihydroxycholestanoyl Coenzyme A (THCA-CoA). In particularnon-limiting embodiments, the racemase inhibitor can be aN-methylthiocarbamate. Further non-limiting examples of AMACR inhibitorsare disclosed in Wilson et al., Mol. Cancer Ther. (2011), 10(5):825-838, the content of which is hereby incorporated by reference in itsentirety.

In certain embodiments, the method of treating a subject comprisesdetermining if the subject is at an increased risk for progressiveprostate cancer, prostate cancer relapse or rapid relapse as describedabove, where if the subject is at increased risk for progressiveprostate cancer, prostate cancer relapse or rapid relapse, thenadministering a therapeutically effective amount of an anti-canceragent. An anti-cancer agent can be any molecule, compound chemical orcomposition that has an anti-cancer effect. Anti-cancer agents include,but are not limited to, chemotherapeutic agents, radiotherapeuticagents, cytokines, anti-angiogenic agents, apoptosis-inducing agents oranti-cancer immunotoxins. In certain non-limiting embodiments, aninhibitor can be administered in combination with one or moreanti-cancer agents. “In combination with,” as used herein, means thatthe inhibitor and the one or more anti-cancer agents are administered toa subject as part of a treatment regimen or plan. This term does notrequire that the inhibitor and/or kinase inhibitor and one or moreanti-cancer agents are physically combined prior to administration northat they be administered over the same time frame. Non-limitingexamples of anti-cancer agents include Abiraterone Acetate,Bicalutamide, Cabazitaxel, Casodex (Bicalutamide), Degarelix, Docetaxel,Enzalutamide, Goserelin Acetate, Jevtana (Cabazitaxel), LeuprolideAcetate, Lupron (Leuprolide Acetate), Lupron Depot (Leuprolide Acetate),Lupron Depot-3 Month (Leuprolide Acetate), Lupron Depot-4 Month(Leuprolide Acetate), Lupron Depot-Ped (Leuprolide Acetate),Mitoxantrone Hydrochloride, Prednisone, Provenge (Sipuleucel-T), Radium223 Dichloride, Sipuleucel-T, Taxotere (Docetaxel), Viadur (LeuprolideAcetate), Xofigo (Radium 223 Dichloride), Xtandi (Enzalutamide), Zoladex(Goserelin Acetate) and Zytiga (Abiraterone Acetate).

In certain embodiments, the method of treating a subject comprisesdetermining if the subject is at an increased risk for progressiveprostate cancer, prostate cancer relapse or rapid relapse as describedabove, where if the subject is at increased risk for progressiveprostate cancer, prostate cancer relapse or rapid relapse, thenperforming one or more of cryotherapy, radiation therapy, chemotherapy,hormone therapy, biologic therapy, bisphosphonate therapy,high-intensity focused ultrasound, frequent monitoring, frequentprostate-specific antigen (PSA) checks and radical prostatectomy. Anon-limiting example of a biologic therapeutic is Sipuleucel-T.Bisphosphonate therapy includes, but is not limited to, clodronate orzoledronate. In certain embodiments, these methods can be used toproduce an anti-cancer effect in a subject.

Hormone therapy can include one or more of orchiectomy and theadministration of luteinizing hormone-releasing hormone (LHRH) analogsand/or agonists, LHRH antagonists, anti-androgens orandrogen-suppressing drugs. Non-limiting examples of LHRH analogs and/oragonists include leuprolide, goserelin and buserelin. Non-limitingexamples of LHRH antagonists include abarelix, cetrorelix, ganirelix anddegarelix. Anti-androgen drugs include, but are not limited to,flutamide, bicalutamide, enzalutamide and nilutamide. Non-limitingexamples of androgen-suppressing drugs include estrogens, ketoconazoleand aminoglutethimide. Frequent monitoring can include PSA blood tests,digital rectal exams, ultrasounds and/or transrectal ultrasound-guidedprostate biopsies at regular intervals, e.g., at about 3 to about 6month intervals, to monitor the status of the prostate cancer. Radicalprostatectomy is a surgical procedure that involves the removal of theentire prostate gland and some surrounding tissue. Prostatectomies canbe performed by open surgery or it may be performed by laparoscopicsurgery.

In certain embodiments, the method of treating a subject comprisesdetermining if a subject is at an increased risk for progressiveprostate cancer by determining the presence of one or more fusion genesselected from the group consisting of TRMT11-GRIK2, SLC45A2-AMACR,MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67, KDM4B-AC011523.2,MAN2A1-FER, PTEN-NOLC1, CCNH-C5orf30 ZMPSTE24-ZMYM4, CLTC-ETV1,ACPP-SEC13, DOCK7-OLR1, PCMTD1-SNTG1 or a combination thereof in asample of the subject, where if one or more fusion genes are detected inthe sample then performing a targeted genome editing technique on one ormore prostate cancer cells within the subject.

In certain embodiments, the method of treating a subject comprisesdetermining if a patient is at an increased risk for prostate cancerrelapse or rapid relapse as described above in section 5.3, where if thesubject is at increased risk for prostate cancer relapse or rapidrelapse then performing a targeted genome editing technique on one ormore prostate cancer cells within the subject.

Genome editing is a method in which endogenous chromosomal sequencespresent in one or more cells within a subject, can be edited, e.g.,modified, using targeted endonucleases and single-stranded nucleicacids. The genome editing method can result in the insertion of anucleic acid sequence at a specific region within the genome, theexcision of a specific sequence from the genome and/or the replacementof a specific genomic sequence with a new nucleic acid sequence. Forexample, and not by way of limitation, the genome editing method caninclude the use of a guide RNA (gRNA), including protospacer adjacentmotifs (PAMs), complementary to a specific sequence within a genome,e.g., a chromosomal breakpoint associated with a fusion gene, to guide anuclease, e.g., an endonuclease, to the specific genomic sequence. Anon-limiting example of an endonuclease includes CRISPR associatedprotein 9 (Cas9). The endonuclease can result in the cleavage of thetargeted genome sequence and allow modification of the genome at thecleavage site through nonhomologous end joining (NHEJ) or homologousrecombination. A non-limiting example of genome editing method isdisclosed in PCT Application No. WO 2014/093701, the contents of whichis hereby incorporated by reference in its entirety.

In certain embodiments, the genome editing method can be used to targetspecific chromosomal breakpoints of a fusion gene present in prostatecancer cells. As normal, non-cancerous, prostate cells do not containthe fusion gene, and therefore do not contain the chromosomal breakpointassociated with the fusion gene, prostate cancer cells can bespecifically targeted using this genome editing method. For example, andnot by way of limitation, genome editing can be used to promotehomologous recombination at a chromosomal breakpoint of a fusion gene inone or more cells of a subject to insert a nucleic acid sequenceencoding the Herpes Simplex Virus 1 (HSV-1) thymidine kinase at thechromosomal breakpoint. In certain non-limiting embodiments, the HSV-1thymidine kinase nucleic acid sequence lacks a promoter and requiresintegration into the genome for expression. In certain embodiments, atherapeutically effective amount of the guanine derivative, ganciclovir,or its oral homolog, valganciclovir, can be administered to a subjectexpressing HSV-1 thymidine kinase. HSV-1 thymidine kinase canphosphorylate and convert ganciclovir and/or valganciclovir into thetriphosphate forms of ganciclovir and/or valganciclovir in the one ormore cells of a subject. The triphosphate form of ganciclovir and/orvalganciclovir is as competitive inhibitor of deoxyguanosinetriphosphate (dGTP) and is a poor substrate of DNA elongation, and canresult in the inhibition of DNA synthesis. The inhibition of DNAsynthesis, in turn, can result in the reduction and/or inhibition ofgrowth and/or survival of prostate cancer cells that contain thetargeted chromosomal breakpoint and the integrated Herpes Simplex Virus1 (HSV-1) thymidine kinase nucleic acid sequence. This genome editingmethod can be used to produce an anti-cancer effect in a subject thathas been determined to have an increased risk for progressive prostatecancer, prostate cancer relapse or rapid relapse.

TABLE 1 siRNA sequences. MAN2A1-FER               MAN2A1                       FER GCAAATACTATTTCAGA

AGTATATAAGGGCA CA (SEQ ID NO: 1) siRNA sequence for MAN2A1-FER:Sense Strand: 5′RCrArGrCrCrUrArUrGrArGrGrGrArArArUrUrUrUrGrGrUGA (SEQ ID NO: 2)Antisense Strand: 5′RUrCrArCrCrArArArArUrUrUrCrCrCrUrCrArUrArGrGrCrUrGrUrU (SEQ ID NO: 3)SLC45A2-AMACR               SLC45A2             AMACR TCCACTAC

AAACTCCAGCTGGGCCCAGAGA (SEQ ID NO: 4) siRNA sequence for SLC45A2-AMACR:Sense Strand: 5′RUrGrCrCrCrUrCrUrUrCrArCrArGrGrUrGrUrCrArUrGrGAG (SEQ ID NO: 5)Antisense Strand: 5′RCrUrCrCrArUrGrArCrArCrCrUrGrUrGrArArGrArGrGrGrCrArUrG (SEQ ID NO: 6)MTOR-TP53BP1                 MTOR                TP53BP1 TGTCAGAATCC

TCAGTGGAATCTGCT CCTGC (SEQ ID NO: 7) siRNA sequence for MTOR-TP53BP1:Sense Strand: 5′RGrUrCrArGrGrArUrUrCrCrUrUrGrUrUrCrUrGrGrGrArATG (SEQ ID NO: 8)Antisense Strand: 5′RCrArUrUrCrCrCrArGrArArCrArArGrGrArArUrCrCrUrGrArCrUrU (SEQ ID NO: 9)TMEM135-CCDC67              TMEM135             CCDC67 TTTT

CAACTCCAACAGGTGGAAGAGTACCA (SEQ ID NO: 10)siRNA sequence for TMEM135-CCDC67: Sense Strand: 5′RGrArCrUrCrArCrCrArArGrGrGrCrArArArUrArArGrArAGC (SEQ ID NO: 11)Antisense Strand: 5′RGrCrUrUrCrUrUrArUrUrUrGrCrCrCrUrUrGrGrUrGrArGrUrCrUrU (SEQ ID NO: 12)CCNH-C5orf30                CCNH              C5ORF30 TGTCACAGTTACTAGATA

AAAATTATTATGT CT (SEQ ID NO: 13) siRNA sequence for CCNH-C5orf30:Sense Strand: 5′RArUrGrArArArArUrArCrCrUrGrGrArGrUrArGrArArCrAGA (SEQ ID NO: 14)Antisense Strand: 5′RUrCrUrGrUrUrCrUrArCrUrCrCrArGrGrUrArUrUrUrUrCrArUrUrA (SEQ ID NO: 15)KDM4B-AC011523.2               KDM4B                     AC011523.2AACTACCTGCACTTTG

AGCCTGGATCTGAGA GA (SEQ ID NO: 16) siRNA sequence for KDM4-AC011523.2:Sense Strand: 5′ RGrArGrCrCrUrArArGrUrCrCrUrGrGrArCrArGrUrArArGCA(SEQ ID NO: 17) Antisense Strand: 5′RUrGrCrUrUrArCrUrGrUrCrCrArGrGrArCrUrUrArGrGrCrUrCrCrC (SEQ ID NO: 18)TRMT11-GRIK2              TRMT11                  GRIK2 AGCATCTGGAG

ATGTGGAATCTGGCCCAATG GGAGCTG (SEQ ID NO: 19)siRNA sequence for TRMT11-GRIK2: Sense Strand: 5′RCrCrGrCrCrUrGrCrCrGrGrUrGrGrUrArUrUrUrUrUrGrAAT (SEQ ID NO: 20)Antisense Strand: 5′RArUrUrCrArArArArArUrArCrCrArCrCrGrGrCrArGrGrCrGrGrArA (SEQ ID NO: 21)LRRC59-FLJ60017               LRRC69                   FLJ60017CTGCTTGGATGAGAAGCAGTGTAAGCAGTGTGC

CTC AATGGCTG (SEQ ID NO: 22) siRNA sequence for LRRC59-FLJ60017:Sense Strand: 5′RArCrArArGrGrUrGrArCrUrGrGrArArGrCrArCrCrUrGrCTC (SEQ ID NO: 23)Antisense Strand: 5′RGrArGrCrArGrGrUrGrCrUrUrCrCrArGrUrCrArCrCrUrUrGrUrUrU (SEQ ID NO: 24)PTEN-NOLC1              PTEN                          NOLC1AAGCCAACCGATACTT

TGCCAATGCCTCTTCCCTCTTA GAC (SEQ ID NO: 25)siRNA sequence for PTEN-NOLC1: Sense Strand: 5′RCrUrCrCrArArArUrUrUrUrArArGrArCrArCrArGrCrArGGA (SEQ ID NO: 26)Antisense 5′ RUrCrCrUrGrCrUrGrUrGrUrCrUrUrArArArArUrUrUrGrGrAr Strand:GrArA (SEQ ID NO: 27)Head gene is in highlighted in green and tail gene in yellow. Targetedsequences are underlined and bolded.

5.4 Kits

The present invention further provides kits for detecting one or morefusion genes disclosed herein and/or for carrying any one of theabove-listed detection and therapeutic methods.

Types of kits include, but are not limited to, packaged fusiongene-specific probe and primer sets (e.g., TaqMan probe/primer sets),arrays/microarrays, antibodies, which further contain one or moreprobes, primers, or other reagents for detecting one or more fusiongenes of the present invention.

In certain non-limiting embodiments, a kit is provided comprising one ormore nucleic acid primers or probes and/or antibody probes for use incarrying out any of the above-listed methods. Said probes may bedetectably labeled, for example with a biotin, colorimetric, fluorescentor radioactive marker. A nucleic acid primer may be provided as part ofa pair, for example for use in polymerase chain reaction. In certainnon-limiting embodiments, a nucleic acid primer may be at least about 10nucleotides or at least about 15 nucleotides or at least about 20nucleotides in length and/or up to about 200 nucleotides or up to about150 nucleotides or up to about 100 nucleotides or up to about 75nucleotides or up to about 50 nucleotides in length. An nucleic acidprobe may be an oligonucleotide probe and/or a probe suitable for FISHanalysis. In specific non-limiting embodiments, the kit comprisesprimers and/or probes for analysis of at least two, at least three, atleast four, at least five, six, seven, eight, nine, ten, eleven, twelve,thirteen, fourteen of TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1,LRRC59-FLJ60017, TMEM135-CCDC67, KDM4B-AC011523.2, MAN2A1-FER,PTEN-NOLC1, CCNH-C5orf30, ZMPSTE24-ZMYM4, CLTC-ETV1, ACPP-SEC13,DOCK7-OLR1 and PCMTD1-SNTG1.

In certain non-limiting embodiments, the nucleic acid primers and/orprobes may be immobilized on a solid surface, substrate or support, forexample, on a nucleic acid microarray, wherein the position of eachprimer and/or probe bound to the solid surface or support is known andidentifiable. The nucleic acid primers and/or probes can be affixed to asubstrate, such as glass, plastic, paper, nylon or other type ofmembrane, filter, chip, bead, or any other suitable solid support. Thenucleic acid primers and/or probes can be synthesized directly on thesubstrate, or synthesized separate from the substrate and then affixedto the substrate. The arrays can be prepared using known methods.

In non-limiting embodiments, a kit provides nucleic acid probes for FISHanalysis of one or more fusion gene selected from the group consistingof: TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017,TMEM135-CCDC67, CCNH-C5orf30, TRMT11-GRIK2, SLC45A2-AMACR,KDM4B-AC011523.2, MAN2A1-FER, PTEN-NOLC1, MTOR-TP53BP1, ZMPSTE24-ZMYM4,CLTC-ETV1, ACPP-SEC13, DOCK7-OLR1 or PCMTD1-SNTG1. In non-limitingembodiments, a kit provides nucleic acid probes for FISH analysis of oneor more fusion gene selected from the group consisting of: TRMT11-GRIK2,SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67, PTEN-NOLC1and CCNH-C5orf30, and TRMT11-GRIK2, SLC45A2-AMACR, KDM4B-AC011523.2,MAN2A1-FER, MTOR-TP53BP1, ZMPSTE24-ZMYM4, CLTC-ETV1, ACPP-SEC13,DOCK7-OLR1 or PCMTD1-SNTG1. In specific non-limiting embodiments, probesto detect a fusion gene may be provided such that separate probes eachbind to the two components of the fusion gene or a probe may bind to a“junction fragment” that encompasses the boundary between the splicedgenes. In specific non-limiting embodiments, the kit comprises saidprobes for analysis of at least two, at least three, at least four, atleast five, six, seven, eight or all nine of TRMT11-GRIK2,SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67,KDM4B-AC011523.2, MAN2A1-FER, PTEN-NOLC1, CCNH-C5orf30, ZMPSTE24-ZMYM4,CLTC-ETV1, ACPP-SEC13, DOCK7-OLR1 or PCMTD1-SNTG1. An example of FISHanalysis used to identify a fusion gene is provided in Example 1 below.

In non-limiting embodiments, a kit provides nucleic acid primers for PCRanalysis of one or more fusion gene selected from the group consistingof: TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017,TMEM135-CCDC67, PTEN-NOLC1, CCNH-C5orf30, TRMT11-GRIK2, SLC45A2-AMACR,KDM4B-AC011523.2, MAN2A1-FER, MTOR-TP53BP1, ZMPSTE24-ZMYM4, CLTC-ETV1,ACPP-SEC13, DOCK7-OLR1 or PCMTD1-SNTG1. In non-limiting embodiments, akit provides nucleic acid primers for PCR analysis of one or more fusiongene selected from the group consisting of: TRMT11-GRIK2, SLC45A2-AMACR,MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67, PTEN-NOLC1 andCCNH-C5orf30, and TRMT11-GRIK2, SLC45A2-AMACR, KDM4B-AC011523.2,MAN2A1-FER, MTOR-TP53BP1, ZMPSTE24-ZMYM4, CLTC-ETV1, ACPP-SEC13,DOCK7-OLR1 or PCMTD1-SNTG1. In specific non-limiting embodiments, thekit comprises said primers for analysis of at least two, at least three,at least four, at least five, six, seven, eight, nine, ten, eleven,twelve, thirteen, fourteen of TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1,LRRC59-FLJ60017, TMEM135-CCDC67, KDM4B-AC011523.2, MAN2A1-FER,PTEN-NOLC1, CCNH-C5orf30, ZMPSTE24-ZMYM4, CLTC-ETV1, ACPP-SEC13,DOCK7-OLR1 and PCMTD1-SNTG1.

The following Examples are offered to more fully illustrate thedisclosure, but are not to be construed as limiting the scope thereof.

6. EXAMPLE 1: TRANSLOCATION AND FUSION GENE EVENTS IN PROGRESSIVEPROSTATE CANCER 6.1 Abstract

Importance:

Prediction of prostate cancer clinical outcome remains a major challengeafter the diagnosis. An accurate and reproducible test predicting thebehavior of prostate cancer is urgently needed.

Objective:

To identify biomarkers that are predictive of prostate cancer recurrenceor prostate cancer related death.

Design:

Genome DNA and/or total RNA from Nineteen specimens of prostate cancer(T), matched adjacent benign prostate tissues (AT), matched bloods (B)and organ donor prostates (OD) were sequenced. Eight novel fusion geneswere discovered and validated. These 8 novel fusion genes were thenanalyzed on 174 prostate samples, including 164 prostate cancer and 10healthy prostate organ donor samples. Up to 15 years of clinicalfollow-ups on prostate cancer patients were conducted.

Setting:

University of Pittsburgh Medical Center, Presbyterian and ShadysideCampus.

Participants:

One hundred sixty-four prostate cancer patients underwent radicalprostatectomy from 1998-2012 were selected for fusion gene expressionanalysis. 80.5% (132/164) patients had been followed-up for at least 5years.

Main Measure:

To identify the presence of any of the following fusion genes inprostate cancer samples: TMEM135-CCDC67, KDM4B-AC011523.2, MAN2A1-FER,TRMT11-GRIK2, CCNH-C5orf30, SLC45A2-AMACR, MTOR-TP53BP1 andLRRC59-FLJ60017.

Results:

Approximately 90% of men carrying at least one of six of these fusiongenes (TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017,TMEM135-CCDC67 and CCNH-C5orf30) experienced prostate cancer recurrence,metastases and/or prostate cancer-specific death after radicalprostatectomy, while these outcomes occurred in only 36% of men notcarrying those fusion genes. Four fusion genes occurred exclusively inprostate cancer samples from patients who experienced recurrence orprostate cancer related death. The formation of these fusion genes isthe result of genome recombination events.

Conclusion and Relevance:

These findings suggest that the formation of these fusion genes areassociated with prostate cancer recurrence and may drive theprogression.

6.2. Introduction

Despite a high incidence^(1,2), only a fraction of men diagnosed withprostate cancer develop metastases and even fewer die from the disease.The majority of prostate cancers remain asymptomatic and clinicallyindolent. The precise mechanisms for the development of progressive,clinically concerning prostate cancer remain elusive. Furthermore, theinability to predict prostate cancer's potential aggressiveness hasresulted in significant overtreatment of the disease. The dichotomousnature of prostate cancer—a subset of life-threatening malignancies inthe larger background of histological alterations lacking the clinicalfeatures implicit with that label—is a fundamental challenge in diseasemanagement.

To identify genome markers for prostate cancer, whole genome sequencingwas performed on 14 prostate tissue samples from 5 prostate cancerpatients: five prostate cancers (T) from patients who experienced poorclinical outcomes (reoccurrence with fast rise of prostate cancerantigen doubling time (PSADT <4 months)), five matched blood (B) samplesand four matched benign prostate tissues from the prostate cancerpatients (AT) (Table 2). In one patient, normal adjacent prostate tissuewas not available. An average of 200 GB was sequenced per sample toachieve 33 fold coverage of the entire genome. Total RNA from all T andAT samples was sequenced to achieve >1333 (average 400 millionreads/sample) fold coverage per gene. Total RNA from four age-matched,entirely histologically benign prostate tissues harvested from healthyorgan donors was similarly sequenced as a tissue control. The sequencingdata were aligned to human reference genome HG19³. Fusion genes werethen identified and validated. We hypothesize that these fusion genesfrom cancer samples that prove metastatic are associated poor clinicaloutcome for prostate cancer patients. A prediction model for prostatecancer recurrence and short post-operative prostate specific antigendoubling time (PSADT) was built. This model was then applied to 89additional prostate cancer samples from University of Pittsburgh MedicalCenter, 30 samples from Stanford University Medical Center, and 36samples from University of Wisconsin Madison Medical Center withfollow-up ranging from 1 to 15 years. One hundred twenty-seven of thesesamples are from patients who experienced prostate cancer recurrenceafter radical prostatectomy, and 106 are from patients with no evidenceof recurrence for at least 5 years after the surgery. The remaining 46samples are from patients who had less than 5 years of follow-up and hadnot yet experienced biochemical recurrence.

The newly validated fusion genes were then analyzed on 164 prostatecancer samples with clinical follow-up ranging from 2 to 15 years.Seventy-eight of these samples are from patients who experiencedprostate cancer recurrence after radical prostatectomy, while 54 arefrom patients had no recurrence for at least 5 years after the surgery.The remainder samples are from patients who had radical prostatectomyless than 5 years ago. Association of fusion gene expression withprostate cancer recurrence was analyzed.

6.3 Methods

Tissue samples. Nineteen specimens of prostate cancer (T), matchedadjacent benign prostate tissues (AT), matched bloods (B) and organdonor prostates (OD) were obtained from University of Pittsburgh TissueBank in compliance with institutional regulatory guidelines (Table 2).To ensure high purity (L80%) of tumor cells, needle-microdissection wasperformed by pathologists to isolate the tumor cells from adjacentnormal tissues (≥3 mm distance from the tumor). For AT and OD samples,similar needle-microdissections were performed to achieve 80% epithelialpurity. Genomic DNA of these tissues was extracted using a commerciallyavailable tissue and blood DNA extraction kit (Qiagen, Hilden, Germany).The protocols of tissue procurement and procedure were approved byInstitution Board of Review of University of Pittsburgh.

Whole Genome and Transcriptome Sequencing Library Preparation.

To prepare the genomic DNA libraries, 50 ng DNA was subjected to thetagmentation reactions using the NEXTERA DNA sample prep kit (Madison,Wis.) for 5 min at 55° C. The DNA was then amplified with adaptor andsequencing primers for 9 cycles of the following procedure: 95° C. for10s, 62° C. for 30s and 72° C. for 3 min. The PCR products were purifiedwith Ampure beads. The quality of genomic DNA libraries was thenanalyzed with qPCR using Illumina sequencing primers and quantified withAgilent 2000 bioanalyzer. For transcriptome sequencing, total RNA wasextracted from prostate samples using Trizol, and treated with DNAse1.Ribosomal RNA was then removed from the samples using RIBOZERO™ Magnetickit (Epicentre, Madison, Wis.). The RNA was reverse-transcribed to cDNAand amplified using TRUSEQ™ RNA Sample Prep Kit v2 from Illumina, Inc(San Diego, Calif.). The library preparation process such asadenylation, ligation and amplification was performed following themanual provided by the manufacturer. The quantity and quality of thelibraries were assessed as those described in genome DNA librarypreparation.

Whole Genome and Transcriptome Sequencing.

The Illumina whole genome sequencing system was applied to the analysis.The operation procedures strictly followed the manufacturer'sinstructions. Briefly, DNA libraries were hybridized to flowcells andsubjected to primer extension and bridge amplification in an automaticcBot process for 4 h to generate clusters of DNA sequencing templates.These clustered flowcells were then subjected to the sequencing analysisin the Illumina HiSeq2000 system. All samples were sequenced withpaired-end runs for 200 cycles.

Read Alignment.

Whole genome DNA-seq reads from 5 Ts, 4 ATs and 5 Bs were aligned byBWA³ version 1.4.1 against the UCSC hg19 human reference genome allowingmaximal 2 base mismatches per (100 nucleotide) read. After alignment,the average coverage of whole genome is above 30× for all 14 samples.Picard tool (http://picard.sourceforge.net) was applied to removeduplicate reads after the alignment. RNA-seq reads (from 5 T, 4 matchedAT and 4 OD samples) were at an average of 1333× coverage. Wholetranscriptome RNA-seq reads were aligned with the UCSC hg19 referencegenome using Tophat⁴⁻⁶ version 1.4.1. Maximal 2 mismatches per read wereallowed.

Fusion Gene Detection.

To identify fusion gene events, we applied a Fusioncatcher (v0.97)algorithm⁷ on RNA sequencing samples. The analysis results by thesoftware had been validated with high precision rate in breast cancercell lines. Both BOWTIE and BLAT alignment were applied in the analysisand were plotted with CIRCOS software⁸. The preliminary list ofcandidate fusion transcripts are filtered in Fusioncatcher based on theexisting biological knowledge of the literature including: (1) If thegenes are known to be the other's paralog in Ensembl; (2) If one of thefusion transcripts are the partner's pseudogene; (3) If one of thefusion transcripts are micro/transfer/small-nuclear RNA; (4) If thefusion transcript is known to be a false positive event (e.g., Conjoingene database²¹); (5) If it has been found in healthy samples (IlluminaBody Map2.0[http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-513/]); (6) Ifthe head and tail genes are overlapping with each other on the samestrand. Fusion genes were visualized with CIRCOS software⁸ as shown inFIG. 6.

TABLE 2 Relapse Relapse Case TNM Margin Relapse fast simple Gleason AgeGender Race Case 1 T3bN1MX Negative fast f y 7 50s M W Case 2 T3aN0MXNegative slow nf y 7 60s M W Case 3 T2cN0MX Negative fast f y 8 60s M WCase 4 T3bN1MX Negative fast f y 10 50s M W Case 5 T3bN1MX Negative fastf y 10 50s M W Time interval Time to of Length of PSA pre- progressionRadiology follow-up follow-up Additional Case operative (Months) PSADTfollow-up (Months) (Months) treatment Case 1 14.6 1.41 3.7 NEGATIVE 2.7629.09 ADT Case 2 4.1 43.75 39.96 NO 2.56 133.3 RT Case 3 2.38 33.76 2.99NEGATIVE 3.42 33.93 RT Case 4 29.3 1.35 0.93 POSITIVE 1.02 15.48 ADT,FOR BONE CHEMO METASTASIS Case 5 9.17 1.35 1.83 POSITIVE 2.4 149.6 ADTFOR BONE METASTASIS

Machine Learning Classifier to Predict Relapse Status.

8 fusion genes from 5 tumor samples validated by RT-PCR, Sangersequencing and Fluorescence In-situ Hybridization (FISH) analyses wereused as features to predict the relapse status (fast vs non-fast andrelapse vs non-relapse) in a large validation cohort (PSADT<4 months vsPSADT>15 months or non-recurrent). The presence for each fusion pair wascoded either as 1 or 0 to represent whether the fusion gene exist in thesample. Linear discriminant analysis (LDA) was used to build aclassifier. In light of relatively rare occurrence of the fusiontranscripts (4.4%-9.0%) in our 90-sample Pittsburgh training cohort, wealso applied a simple prediction rule based on the presence in anysubset of the eight fusion genes (i.e., a patient is predicted asrecurrence if any fusion transcript in a designated subset exists).Leave-one-out cross validation (LOOCV) was applied to construct themodel and evaluate the prediction performance. ROC curves wereconstructed by varying the parameters in the LDA classifier constructionand the optimal prediction model was selected with the best Youden index(=sensitivity+specificity-1)²², and was then evaluated in a 89-samplePittsburgh test cohort, a 21-sample Stanford test cohort and a 30-sampleWisconsin test cohort. To compare the statistical significance of AUCdifference between two models, a bootstrap test is used to generatep-values²³. To compare accuracy of two models, a test for equalproportions using “prop.test” in R is applied.

To demonstrate the potential translational predictive value of thesefusion transcripts, information of Nomogram estimated five-year PSA freesurvival probability and Gleason scores of the patients was incorporatedinto our prediction models. The following models were generated: (I) 8fusion transcripts alone, (II) Gleason scores alone, (III) Nomogramvalues alone, (IV) Gleason scores+8 fusion transcripts, (V) Nomogramvalues+8 fusion transcripts. Complete information of predictionaccuracy, sensitivity, specificity and Youden index for these eightmodels is available in Tables 7-16.

RT-PCR.

To verify fusion genes detected by transcriptome and whole genomesequencing, total RNA was reverse-transcribed with random hexamer.Double strand cDNA was synthesized as described previously^(9,10). PCRswere performed using primers indicated in Table 3 using the followingcondition: 94° C. for 5 min, followed by 30 cycles of 94° C. for 30seconds, 61° C. for 1 min and 72° C. for 2 min.

TABLE 3 Primer sequences for RT-PCR. Fusion genes SequencesTMEM135-CCDC67 5′-TTGGCATGATAGACCAGTCCC-3/5′-CAGCACCAAGGGAATGTGTAG-3′(SEQ ID NO: 58/SEQ ID NO: 59) Mtor-TP53BP15′-TTGGCATGATAGACCAGTCCC-3/5′-CAGCACCAAGGGAATGTGTAG-3′ (SEQ IDNO: 60/SEQ ID NO: 61) TRMT11-GRIK25′-GCGCTGTCGTGTACCCTTAAC-3/5′-GGTAAGGGTAGTATTGGGTAGC-3′ (SEQ IDNO: 62/SEQ ID NO: 63) CCNH-C5orf305′-CCAGGGCTGGAATTACTATGG-3/5′-AAGCACCAGTCTGCACAATCC-3′ (SEQ IDNO: 64/SEQ ID NO: 65) SLC45A2-AMACR5′-TTGATGTCTGCTCCCATCAGG-3/5′-TGATATCGTGGCCAGCTAACC-3′ (SEQ IDNO: 66/SEQ ID NO: 67) KDM4B-AC011523.25′-AACACGCCCTACCTGTACTTC-3/5′-CTGAGCAAAGACAGCAACACC-3′ (SEQ IDNO: 68/SEQ ID NO: 69) MAN2A1-FER5′-TGGAAGTTCAAGTCAGCGCAG-3/5′-GCTGTCTTTGTGTGCAAACTCC-3′ (SEQ IDNO: 70/SEQ ID NO: 71) LRRC59-FLI600175′-GTGACTGCTTGGATGAGAAGC-3/5′-CCAGCATGCAGCTTTTCTGAG-3′ (SEQ IDNO: 72/SEQ ID NO: 73) TMPRSS2-ERG5′-AGTAGGCGCGAGCTAAGCAGG-3/5′-GGGACAGTCTGAATCATGTCC-3′ (SEQ IDNO: 74/SEQ ID NO: 75) β-actin5′-TCAAGATCATTGCTCCTCCTGAGC-3/5′-TGCTGTCACCTTCACCGTTCCAGT-3′(SEQ ID NO: 76/SEQ ID NO: 77)

Fluorescence In-Situ Hybridization.

Formalin-fixed and paraffin-embedded tissue slides (5 microns) wereplaced in 2×SSC at 37° C. for 30 min. Slides were then removed anddehydrated in 70% and 85% ethanol for 2 min each at room temperature,and air dried. The DNA from the selected clones (Table 4) was extractedusing Nucleobond Ax kit (Macherey-Nagel, Easton, Pa.). Thebiotin-labeled probes were prepared using standard nick-translationprocedure and hybridized to sample slides as describedpreviously^(11, 12).

TABLE 4 Bacterial artificial chromosome clone for FISH. Fusion genesProbe 1 Probe 2 TMEM135-CCDC67 RP11-80F20 RP11-1034E22 Mtor-TP53BP1RP4-647M16 RP11-114F23 TRMT11-GRIK2 RP11-92N18 RP11-70I17 CCNH-C5orf30RP11-111M24 RP11-244M13 SLC45A2-AMACR RP11-179D3 RP11-1072I21 KDM4B-AC011523.2 RP11-241K5 RP11-655K24 MAN2A1-FER RP11-452L20 RP11-328A14LRRC59-SLC35B3 RP11-269I10 RP11-360D22 LRRC59-FLJ60017 RP11-269I10CTD-2116N11

6.4. Results

Fusion Genes Discovered by RNA and Whole Genome Sequencing.

A total of 76 RNA fusion events were identified in prostate cancersamples by the Fusioncatcher⁷ program. Thirteen of these fusion eventswere suggested by genome sequencing. To control for tissue-based fusiongene events, fusion genes present in any of the four age-matched organdonor prostate tissues were eliminated (Table 5). Further, fusion geneswith less than 20 kb between each element and read in the cis directionwere also eliminated. As a result of this filtering, 28 of 76 fusiongene events were identified as prostate cancer specific (Table 6 andFIG. 6). Among these fusion events, TMPRSS2-ERG, the most commonprostate cancer fusion gene¹³⁻¹⁵, was found in two prostate cancersamples. Majority of the fusion events identified are novel and notreported in the literature. None of the 29 fusion genes were identifiedin the matched AT transcriptome analysis. To validate these fusiongenes, RT-PCR was performed using primers specific for fusion generegions encompassing the fusion breakpoints and the PCR products weresequenced. Eight of these fusion gene events were validated throughsequencing (FIG. 1).

Five of the eight fusion events resulted in truncation of a driver geneand frameshift in translation of a passenger gene. One of the fusiongenes produced a truncated cyclin H and an independent open readingframe of a novel protein whose function is not known. Two fusion events,however, produced chimera proteins that possibly retain at least partialfunction of both genes. One of these fusion products is N-terminus 703amino acids of a-Mannosidase 2A (MAN2A1) fusing to the C-terminus 250amino acids of FER, a Feline tyrosine kinase. The fusion protein retainsthe glycoside hydrolase domain but has its manosidase domain replacedwith a tyrosine kinase domain from FER. Another fusion protein productproduces a chimera of membrane-associated transporter protein (SLC45A20)and alpha-methylacyl-CoA racemase (AMACR). The chimera protein has 5 ofits 10 transmembrane domains deleted from SLC45A2 and replaced withmethyl-acyl CoA transferase domain from AMACR. Interestingly, bothMAN2A1-FER and SLC45A2-AMACR fusions are in the trans-direction,eliminating the possibility of a fusion event from simple chromosomedeletion or collapse of extremely large RNA transcript.

Fluorescence In Situ Hybridization Suggests Genome RecombinationUnderlying Fusion Gene Formation.

To investigate the mechanism of these fusion events, fluorescence insitu hybridization (FISH) was performed on prostate cancer tissues wherethe fusion gene was present. Using the probes surrounding MAN2A1breakpoint, a physical separation of signals between 5′ and 3′ MAN2A1 incancer cells containing the fusion gene was observed, in contrast to theoverlapping nature of these signals in the wild type alleles in normalprostate epithelial cells (FIG. 2). Similar “break-apart” hybridizationoccurred in SLC45A2-AMACR positive prostate cancer samples (FIG. 2B).These findings indicate that MAN2A1-FER and SLC45A2-AMACR fusions arethe result of chromosome recombination. Interestingly, in prostatecancer cells containing “break-apart” signals of MAN2A1, only 31% of thecells retained the 3′ end signal, suggesting that the recombination ofgenome DNA in most prostate cancer cells results in truncation of theC-terminus of MAN2A1. A similar “collateral loss” of the N-terminus ofAMACR was found in prostate cancer cells expressing SLC45A2-AMACR fusion(29% retaining the N-terminus signal of AMACR). Other FISH analysesconfirm that genome translocations occur in cancer cells expressingTRMT11-GRIK2, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM137-CCDC67,CCNH-C5orf30 and KDM4B-AC011523.2 fusion genes (FIGS. 2C-G). Thesefusion genes are either separated by a large segment of genome DNA(TRMT11-GRIK2, TMEM135-CCDC67, CCNH-C5orf30 and KDM4B-AC011523.2) orlocated in separate chromosomes (MTOR-TP53BP1 and LRRC59-FLJ60017). Thejoining signals of hybridizations in prostate cancer cells suggest thatthese fusion genes were relocated to juxtapose to their fusion partners.Finally, genomic breakpoints were identified in 3 fusion pair throughSanger sequencing of the cancer genomic DNA (CCNH-C5orf30,TMEM135-CCDC67 and LRRC59-FLJ60017) (FIG. 11).

Fusion Genes Association with Prostate Cancer Recurrence.

A genomic alteration in prostate cancer without clinical consequence isof limited significance. Therefore, the association of these fusiongenes with prostate cancer progression was investigated in prostatecancer specimens obtained from 213 men and from entirely benign prostatetissues obtained from 10 organ donors free of urological disease aged 20to 70. The prostate cancer samples were linked to the clinical outcomesafter radical prostatectomy: those with no detectable prostate specificantigen (PSA) recurrence after a minimum of five years of observation,those whose clinical outcomes remain unknown and those who had anobserved PSA recurrence within five years. For 179 of the 223 prostatecancer samples, clinical outcome data after radical prostatectomy wereavailable, and 81 had no detectable prostate specific antigen (PSA)recurrence after a minimum of five years of follow-up, while 98developed biochemical recurrence (defined as a measurable PSA >0.2ng/ml). Only 7.4% (6/81) primary prostate cancers expressed one of thefusion genes in non-recurrent patients. In contrast, 52% (51/98) primaryprostate cancers expressed at least one fusion in patients who developedrecurrence (FIG. 3 and FIG. 7A). No fusion genes were detected in benignprostate tissues obtained from healthy organ donors (FIG. 7B). Threefusion events were observed exclusively in recurrent prostate cancerafter radical prostatectomy (TRMT11-GRIK2, MTOR-TP53BP1 andLRRC59-FLJ60017; FIGS. 3A and B).

Fisher's exact test showed a significant difference in recurrent statusbetween patients with at least one of the 8 fusion transcripts and thosewithout (p=6.8×10⁻¹⁶). In the combined UPMC, Stanford and Wisconsin datasets, 91% (69/76) of patients positive for one of the fusion transcriptsexperienced prostate cancer recurrence in 5 years after prostateresection. Based on the hypothesis that the presence of at least one ofthe 8 fusion transcripts would indicate a recurrence for a prostatecancer patient, a prostate cancer prediction model was built and tested,using 90 randomly selected prostate cancer samples from University ofPittsburgh Medical Center (training set). This training cohort yieldedan accuracy of prostate cancer recurrence prediction of 71% with 89%specificity and 58% sensitivity (p<0.005) (FIG. 12A, Table 10). Whenthis model was applied to a separate cohort of 89 samples (test set),the model correctly predicted recurrence in 70% of patients. To furthervalidate this model, we tested its performance in a 30-patient (21 withqualified clinical follow-up) cohort from Stanford University MedicalCenter and a 36-patient (30 with qualified clinical follow-up) cohortfrom University of Wisconsin Madison Medical Center (FIG. 3, FIG. 8 andFIG. 9). Once again, the model correctly predicted recurrence with 76.2%accuracy and with 89% specificity and 67% sensitivity on the prostatecancer cohort from Stanford, and 80% accuracy and with 100% specificityand 63% sensitivity on the cohort from Wisconsin (Table 11).

Similar to the dichotomous nature of prostate cancer in general,recurrent prostate cancer can progress in an indolent or aggressivemanner. A PSA doubling time (PSADT) less than four months after radicalprostatectomy is strongly associated with the early development ofmetastatic disease and prostate cancer-specific death, whereas theseevents are rare and remote in men with a PSADT of greater than 15months^(16, 17). Strong association was found between the fusion genes(e.g., TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017,TMEM135-CCDC67 and CCNH-C5orf30) with prostate cancer recurrence(p=4.2×10⁻⁹) and a PSADT less than four months (p=6×10⁻⁹). To examinewhether these fusion gene events have prognostic value for prostatecancer clinical outcome, receiver operator curve (ROC) analyses withvarying weights of fusion genes were performed. As shown in FIG. 3C, thepanel of eight fusion genes correctly predicted 74.4% for PSA doublingtime less than four months in the 90-sample training cohort, and 67% forprostate cancer recurrence. To optimize the prediction model, six fusiongenes were selected for an improved association with disease-freesurvival after radical prostatectomy. When the same algorithm wasapplied to a separate 89-sample test set from University of PittsburghMedical Center and 21-sample cohort from Stanford University MedicalCenter, the prediction rate for PSADT<4 months was found to be 78% and71%, respectively (FIG. 4B). As shown in FIG. 3D, 89.5% of patients hadan observed disease recurrence within five years of radicalprostatectomy if they carried any of the six fusion genes. In addition,and as shown in FIG. 4C, 84.2% of patients had an observed diseaserecurrence within five years of radical prostatectomy if they carriedany of the eight fusion genes. No patient survived five years withoutrecurrence if their primary prostate cancer contained a TRMT11-GRIK2 orMTOR-TP53BP1 gene fusion. In contrast, 68% patients were free of diseaserecurrence if any of the novel fusion genes were not detected in theirprimary prostate cancer. Similar findings were also identified in theStanford cohort: 88.9% patients experienced recurrence of prostatecancer if they carried any fusion transcript, while 66.7% patients werefree of the disease recurrence if they are negative.

TABLE 5 Fusion gene 1 Fusion_gene2 read pairs Validation Status SORBS1RP11-476E15.3 25 AHCY RP11-292F22.3 25 DCUN1D3 ERI2 12 MACF1 KIAA0754 11C10orf68 CCDC7 11 RT-PCR and sequencing RP11-166D19.1 BLID 7 ASS1 ASS1P96 BACH1 BACH1-IT1 6 RT-PCR MPDZ RP11-272P10.2 5 LIG3 RP5-837J1.2 4 ACAD8GLB1L3 4 RT-PCR IGSF9B RP11-259P6.1 3 EYA1 RP11-1102P16.1 3 TTC33 PRKAA13 RT-PCR DNAH1 GLYCTK 3 PSPC1 ZMYM5 3 HSP90AB3P RP11-759L5.2 3 LSAMPRP11-384F7.2 3 RNF4 FAM193A 81 RT-PCR AHCY RP11-292F22.3 9 LSAMPRP11-384F7.2 8 CBLL1 AC002467.7 4 FNBP4 Y_RNA 4 TBCE RP11-293G6_A.2 4TRIM58 RP11-634B7.4 4 DCUN1D3 ERI2 4 PHPT1 MAMDC4 3 TRIP6 SLC12A9 3NAT14 ZNF628 3 TLL2 RP11-35J23.5 3 UFSP2 Y_RNA 3 TSPAN33 Y_RNA 3 CADM3DARC 3 KIF27 RP11-213G2.3 3 RABL6 KIAA1984 3 ZNF615 ZNF350 3 ZYG11ARP4-631H13.2 3 RP11-522L3.6 MTND4P32 3 MTND3P10 AC012363.10 3RP11-464F9.1 BMS1P4 3 RNF4 FAM193A 14 RT-PCR GBP3 Y_RNA 3 NACA PRIM1 1AHCY RP11-292F22.3 3 GBP3 Y_RNA 3 HARS2 ZMAT2 2 RT-PCR and sequencingEED C11orf73 1 RT-PCR CNPY3 RP3-475N16.1 1 RT-PCR RN7SL2 Metazoa_SRP 1SLC16A8 BAIAP2L2 2 RT-PCR KLK4 KLKP1 2 RT-PCR and sequencing ZNF137PZNF701 1 RT-PCR AZGP1 GJC3 1 RT-PCR USP7 RP11-252I13.1 1 TRRAPAC004893.1l 1 C6orf47 BAG6 1 RT-PCR TTTY15 USP9Y 9 AC005077.12 LINC001742 ADCK4 NUMBL 2 ZNF606 C19orf18 2 SLC45A3 ELK4 3 RT-PCR and sequencing

The most frequent fusion events in prostate cancer are TRMT11-GRIK2(7.9%, or 22/279) and SLC45A2-AMACR (7.2%, or 20/279) (FIGS. 3A, 7-9).TRMT11-GRIK2 fusion represents a giant truncation of TRMT11, a tRNAmethyltransferase, and elimination of GRIK2, a glutamate receptor butreported to possess tumor suppressor activity¹⁸. Indeed, GRIK2 was notexpressed in prostate cancer samples that contain TRMT11-GRIK2 fusions,while it was detected in organ donor prostate samples (FIG. 10). Only 4of 14 samples with TRMT11-GRIK2 expressed full length non-fusion TRMT11.Thus, the fusion event of TRMT11-GRIK2 represents a loss of functioninstead of a gain.

Combining Detection of Fusion Transcripts and Clinical/PathologicalParameters Improved the Prediction Rate of Prostate Cancer Recurrence.

Prostate cancer samples with at least one fusion transcript correlatewith more advanced stage of prostate cancer (p=0.004), Lymph nodeinvolvement status (P=0.005) and lower nomogram scores (p=0.0003) (Table12). Gleason grading alone produced a prostate cancer recurrenceprediction rate of 61.1%, with 85.7% specificity and 39.6% sensitivityin the 90-sample UPMC training cohort, when Gleason≥8 was used as cutoffto predict prostate cancer recurrence. The Gleason model yieldedprediction accuracy ranging from 57-60% in 3 separate testing cohorts(Tables 13 and 14). However, when fusion transcript status was combinedwith Gleason Grade>8, improvement of prediction was found for all 4cohorts: 72% for the UPMC training cohort, 74% for the UPMC test cohort,76% for the Stanford cohort and 90% for the Wisconsin cohort. ROC showeda significant larger AUC (area under the curve) (0.84 versus 0.67,P=6.6×10−7) and higher testing accuracy (77.7% versus 59.7%, P=0.0019)(FIG. 5A) when Gleason score was combined with detection of any of 8fusion transcripts. Similarly, Nomogram prediction of prostate cancerrecurrence has the best accuracy of 76% with 68.8% sensitivity and 83.3%specificity in the analysis of 90-sample UPMC training cohort (Table15). When this model was applied to UPMC testing, Stanford and Wisconsincohorts independently, the results showed that the prediction accuracyranged from 60% to 75% among the 3 cohorts (Table 16). When Nomogram wascombined with the status of 8 fusion transcripts using LDA technique tobuild a classifier, the accuracy of prediction improves to 81-83% amongthe testing cohorts (Table 16). ROC showed an increase of AUC from 0.76to 0.87 (P=0.0001) and an improvement of accuracy from 69% to 81%(P=0.026, FIG. 5B). As a result, we concluded that classifier combiningNomogram and the 8 fusion gene panel generated the best predictionaccuracy that outperforms each diagnostic tool alone.

6.5. Discussion

Transcriptome and whole genome sequencings revealed numerous fusion RNAtranscripts occurring not just in prostate cancer but also in healthyorgan donor prostate samples (Table 17). Some of these fusion events areverifiable by sequencing on the cDNA products. The functions of thesenew transcripts are not known. Since most of these chimeric RNAtranscripts in healthy individuals are the splicing products of twoadjacent genes, they are likely the new isoforms of the existing genes.These previously defined independent “genes” in the transcript could beone of the preferred spliced isoforms of the existing larger genes.

TABLE 6 Putative fusion transcripts from 5 prostate cancer samples 1TFusion Gene 1 Gene2 in Fusion gene 1 gene2 breakpoint breakpoint ReadsDNAseq Distance TMPRSS2 ERG 21: 42870046: − 21: 39817544: − 8 2 3052502FZD4 RP11- 11: 86665843: − 11: 86633140: − 7 0 32703 736K20.5 ZNF720RP11- 16: 31734674: +  1: 247363495: − 3 0 Inf 488L18.4 RP11-356O9.1TTC6 14: 38033571: + 14: 38075868: + 12  0 42297 IGLV2-8 IGLL5 22:23165779: + 22: 23235961: + 5 0 70182 RP11- KLHL3  5: 137150022: −  5:137056273: − 3 0 93749 381K20.2 ADAP2 RNF135 17: 29286022: + 17:29311635: + 3 0 25613 LRRC59 FLJ60017 17: 48469759: − 11: 63129852: + 37 Inf RIPK1 SERPINB9  6: 3064293: +  6: 2900855: − 5 24  163438 2TFusion Gene 1 Gene2 in Fusion gene 1 gene2 breakpoint breakpoint Readpairs DNAseq Distance MTOR TP53BP1 1: 11290982: − 15: 43773220: − 12 2Inf 3T Fusion Gene 1 Gene2 in Fusion gene 1 gene2 breakpoint breakpointRead pairs DNAseq Distance MAN2A1 FER  5: 109153139: +  5: 108380381: +7 4 772758 KDM4B AC011523.2 19: 5047680: + 19: 51354167: + 7 0 46306487TRMT11 GRIK2  6: 126307768: +  6: 102069824: + 11  0 24237944 NAP1L1CCDC88C 12: 76444311: − 14: 91850880: − 3 2 Inf RP11- H2AFV 15:93277091: −  7: 44874151: − 6 0 Inf 386M24.4 CCNH C5orf30  5: 86697519:−  5: 102601609: + 3 8 15904090 UBA52 CTA- 19: 18685741: +  7:252729331: − 3 3 Inf 242H14.1 C1orf196 KAZN  1: 14507087: +  1:14925479: + 3 0 418392 MTIF2 AL592494.3  2: 55473480: −  1: 121244615: +6 0 Inf RP11- PPP2R5C  3: 52408762: + 14: 102368056: + 3 2 Inf 168J18.6RPL38 AC007283.4 17: 72205448: +  2: 202027232: − 3 0 Inf ACSS1 APMAP20: 24988402: − 20: 24964655: − 3 0 23747 4T Fusion Gene 1 Gene2 inFusion gene 1 gene2 breakpoint breakpoint Read pairs DNAseq DistanceRP11- ACACB 12: 109551220: + 12: 109577202: + 4 0 25982 443D10.3 SLC45A2AMACR  5: 33982341: −  5: 34006004: − 3 0 23663 RP11-550F7.1 CAP1  3:76483671: +  1: 40529899: + 7 9 Inf TMC5 CCP110 16: 19508485: + 16:19539189: + 6 0 30704 TLK2 RP11- 17: 60631098: +  7: 128248237: + 6 126 Inf 274B21.1 TMEM135 CCDC67 11: 87030419: + 11: 93127625: + 7 26 6097206 5T Fusion Gene 1 Gene2 in Fusion gene 1 gene2 breakpointbreakpoint Spanning_pairs DNAseq Distance TMPRSS2 ERG 21: 42870046: −21: 39947671: − 12 2 2922375

This analysis reveals significant number of cancer specific fusion geneevents. These fusions are not detectable in either organ donor prostateor benign prostate tissues from prostate cancer patients. Most of thesefusion transcripts appear to express in low abundance, with only anaverage 6.6 reads of these fusion transcripts detected in >1333×sequencing. Indeed, when the coverage was reduced to 600× in simulationstudies, only MTOR-TP53BP1 was detected consistently. Thecharacteristics of these fusion genes are that they either have a largedistance between the joining genes or have trans-direction of fusionthat could only occur when chromosome recombination happens. In eitherscenario, DNA alteration in genome level must be the underlyingmechanism.

Although the association between the eight novel fusion transcripts andprostate cancer recurrence is striking, the biological roles of thesefusion transcripts are not yet elucidated. Given the known function ofthe genes contributing to the fusion transcripts, their formation mayhave impact on several cell pathways such as RNA stability²⁴(TRMT11-GRIK2), protein glycosylation²⁵ (MAN2A1-FER), cell cycleprogression^(26,27, 28) (CCNH-C5orf50 and MTORTP53BP1), fibroblastgrowth factor nuclear import²⁹ (LRRC59-FLJ60017), histonedemethylation³⁰ (KDM4B-AC011523.2), and fatty acid metabolism³¹(SLC45A2-AMACR). Many of these pathways appear to be fundamental to cellgrowth and survival.

Two of the fusion genes are of particular interest: MAN2A1-FER andSLC45A2-AMACR. First, MAN2A1 is a mannosidase critical in glycosylationof proteins¹⁹. It is usually located in Golgi apparatus. The truncationin MAN2A1-FER replaces the mannosidase domain with a tyrosine kinasedomain from FER²⁰, while leaves the glycosyl transferase domain intact.The chimera protein likely loses the mannosidase function. The newkinase domain in MAN2A1-FER may confer the chimera protein a tyrosinekinase activity. Thus, the impact of this fusion gene could be profound:abnormal glycosylation and phosphorylation in hundreds of secreted orplasma membrane proteins. It may impact on cell-cell interactions andsignal transduction, and generate a new immune response to the cancercells. Second, AMACR is a racemase that catalyzes 2R stereoisomers ofphytanic and pristanic acid to their S counterparts. AMACR is essentialfor β-oxidation of branch fatty acid in mitochondria. SLC45A2 is atransmembrane solute carrier known for its protective role in melanoma.SLC45A2-AMACR chimeric protein has 5 transmembrane domains of SLC45A2truncated and replaced with a largely intact racemase. SLC45A2-AMACRalso loses the mitochondria target site in AMACR. Presumably, the fusionprotein would be located in the plasma membrane. It is of interest thatall prostate cancer samples with SLC45A2-AMACR fusion proved highlyaggressive. Identification of the signaling pathways of this chimericprotein may gain critical insight into the behavior of prostate cancer.

Even though the prevalence of each fusion transcript in prostate cancersamples is low (ranging from 2.9% to 7.9%), up to 60% of prostatecancers that later recurred and had short PSADT were positive for atleast one of these fusion transcripts. The specificity of these fusiontranscripts in predicting prostate cancer recurrence appears remarkablyhigh, ranging from 89-100% among 4 separate prediction cohorts. Therewere no long term recurrence-free survivors if the primary tumorcontained either TRMT11-GRIK2, MTOR-TP53BP1 or LRRC59-FLJ60017 fusiontranscripts.

To our knowledge, this is the first report showing that a set of fusiongenes is strongly associated with poor prognosis of prostate cancer.This discovery may have salient impact on clinical practice in light ofthe limit of serum PSA and Gleason's grading from biopsy samples inpredicting prostate cancer clinical outcome. Detection of one of theseprostate cancer recurrence association fusion genes in prostate cancersample may warrant a more aggressive treatment regimen. The fusion RNAand chimera proteins validated in this study may lay down the foundationfor future molecular targeting therapy for prostate cancer patientscarrying these genes.

TABLE 7 Clinical and pathological characteristics of 213 cases ofprostate cancer from UPMC cohort Length of Time to follow- RecurrenceRecurrence PSA pre- progession PSADT Radiology follow- up AdditionalSample Type TNM Margin Recurrence fast simple Gleason Age Sex Raceoperative (Months) (months) up (Months) Treatment 11462T T T3aN0MXNegative none nf n 7.0 50s M W 25.0 N/A N/A NEGATIVE 158.0 None 1199T TT3bN0MX Negative slow nf y 8.0 50s M W 40.0 15.0 33.7 NEGATIVE 150.0 NK13745T T T1cN0MX Negative none nf n 7.0 60s M W 6.8 N/A N/A NO 151.0None 14304T T T2BN0MX Negative none nf n 6.0 50s M W 7.8 N/A N/A NO156.0 None 14878T T T2bN0MX Negative none nf n 8.0 60s M W 6.2 N/A N/ANO 151.0 None 15463T T T2bN0MX Negative none nf n 7.0 60s M W 7.8 N/AN/A NO 149.0 None 15733T T T2bN0MX Negative none nf n 7.0 50s M W 6.4N/A N/A NO 152.0 None 15875T T T3bN0MX Negative none nf n 7.0 40s M W5.6 N/A N/A NO 154.0 None 15922T T T3aN0MX Negative none nf n 7.0 60s MW 16.0 N/A N/A NO 154.0 None 16464T T T3bN0MX Negative slow nf y 7.0 60sM W 8.5 88.5 24.6 NEGATIVE 149.0 NK 16947T T T3aN1MX Negative slow nf y8.0 70s M W 6.1 31.0 15.6 NEGATIVE 148.0 NK 19381T T T2bN0MX Negativenone nf n 6.0 50s M AA 2.5 N/A N/A NO 154.0 None 1942T T T3bN0MXPositive fast f y 9.0 60s M W 7.5 80.1 14.8 NEGATIVE 157.0 NK 19PR530T TT2cN0MX Negative ND ND ND 7.0 60s M W 4.4 N/A N/A not done 21.0 None1AF8378T T T3aN0MX Negative none nf n 6.0 60s M W 12.9 N/A N/A NO 153.0None 23FB120T T T3bN0MX Negative none nf n 7.0 60s M W 11.4 N/A N/ANEGATIVE 104.0 None 23HB021T T T2bN0MX Negative Fast f y 7.0 50s M W 6.423.0 3.0 NEGATIVE 78.0 ADT, RT 23R19T T T2bN0MX Negative none nf n 7.050s M W 7.2 N/A NA NO 151.0 None 23HB8346T T T2cN0MX Negative ND ND ND6.0 60s M W 7.3 N/A N/A NO 34.0 None 25265T T T3bN0MX Negative none nf n7.0 60s M W 3.4 N/A N/A NO 156.0 None 25313T T T3bN0MX Negative none nfn 8.0 50s M W 9.5 N/A N/A NO 156.0 None 2644T T T3aN0MX Negative slow nfy 9.0 50s M W 11.2 5.9 31.2 NEGATIVE 164.0 NK 2671T T T2cN0MX Positiveslow nf y 7.0 60s M W 8.9 17.0 17.0 NEGATIVE 164.0 NK 28278T T T3AN0MXNegative none nf n 7.0 50s M W 4.0 N/A N/A NO 157.0 None 29671T TT3AN0MX Negative slow nf y 7.0 60s M W 8.9 15.4 15.4 NEGATIVE 155.0 NK29825T T T3aN0MX Negative none nf n 7.0 50s M W 12.0 N/A N/A NEGATIVE159.0 None 2HB568T T T3bN0MX Negative fast f y 7.0 60s M W 5.7 24.1 3.9NEGATIVE 70.3 ADT, RT 2HB591T T T3bN1MX Negative fast f y 7.0 60s M W18.3 1.5 3.8 POSITIVE FOR 47.0 ADT, BONE AND CHEMO HEPATIC METASTASIS21B483T T T2bN0MX Negative fast f y 7.0 50s M W 6.2 1.7 1.9 NO 58.0 ADT,CHEMO 2K98- T T3AN0MX Positive none nf n 7.0 60s M W 8.6 N/A N/A NO158.0 None 8378T 33PR053T T T3bN1MX Negative fast f y 8.0 60s M W 21.01.0 0.4 bone metastasis 16.0 CHEMO 34PR227T T T3bN0MX Negative none nf n7.0 60s M W 11.6 N/A N/A NO 123.0 None 34T T T2CN0MX Positive none nf n7.0 50s M U 3.6 N/A N/A NO 159.0 None 3D994336T T T2bN0MX Negative nonenf n 6.0 60s M W 6.6 N/A N/A NEGATIVE 164.0 None 3G989122T T T2bN0MXNegative none nf n 7.0 50s M W 9.0 N/A N/A NO 164.0 None 3K5772T TT3bN0MX Negative none nf n 7.0 60s M U 6.7 N/A N/A NO 160.0 None3M-11462T T T3aN0MX Negative none nf n 7.0 50s M W 22.0 N/A N/A NEGATIVE158.0 None 3Q-10614T T T3bN0MX Negative none nf n 7.0 70s M W 12.5 N/AN/A NO 77.0 None 4308T T T1CN0MX Negative none nf n 6.0 60s M W 12.4 N/AN/A NO 153.0 None 4336T T T1cN0MX Positive slow nf y 6.0 60s M W 2.521.7 22.0 NEGATIVE 165.0 NK 4L98- T T3aN0MX Negative none nf n 7.0 60s MW 12.2 N/A N/A NO 78.0 None 27086T 5396T T T2bN1MX Negative none nf n9.0 60s M W 8.9 N/A N/A NO 156.0 None 54IB289T T T2bN0MX Negative nonenf n 6.0 50s M W 9.6 N/A N/A not done 89.0 None 562T T T2bN0MX Negativenone nf n 6.0 60s M W 11.3 N/A N/A NO 157.0 None 56FB76T T T3bN0MXNegative none nf n 6.0 60s M W 6.6 N/A N/A not done 137.0 None 6647T TT3AN0MX Negative none nf y 7.0 40s M AA 6.1 95.6 45.5 NEGATIVE 150.0 NK678T T T2bN0MX Negative none nf n 7.0 60s M W 5.3 N/A N/A NO 152.0 None67R13T T T2bN0MX Negative none nf n 6.0 60s M W 10.8 N/A N/A NO 145.0None 6837T T T3aN0MX Negative slow nf y 6.0 70s M W 10.4 87.4 15.4NEGATIVE 155.0 NK 7221T T T3bN0MX Negative fast f y 7.0 50s M W 13.516.6 2.4 POSITIVE FOR 124.0 ADT, BONE CHEMO, METASTASIS RT 7270T TT3BN1MX Negative none nf n 9.0 70s M W 15.9 N/A N/A NO 98.0 None 7504T TT3bN0MX Positive none nf n 9.0 70s M U 10.5 N/A N/A NO 143.0 None78HB340T T T3b1N0MX Negative ND ND ND 7.0 60s M W 9.6 N/A N/A not done14.0 None 7943T T T3AN0MX Positive none nf n 7.0 60s M W 9.6 N/A N/A NO137.0 None 828142T T T2bN0MX Negative none nf n 8.0 60s M W 7.4 N/A N/ANO 160.0 None 832972T T T2bN0MX Negative none nf n 10.0 60s M W 7.5 N/AN/A NO 160.0 None 842620T T T2bN0MX Negative none nf n 7.0 60s M W 7.7N/A N/A NO 159.0 None 8432T T T2aN0MX Positive none nf n 7.0 50s M W 6.6N/A N/A NO 166.0 None 84375T T T2bN0MX Negative none nf n 6.0 60s M W6.8 N/A N/A NO 161.0 None 84876T T T2bN0MX Negative none nf n 7.0 60s MW 8.9 N/A N/A NO 160.0 None 849731T T T2bN0MX Negative none nf n 7.0 50sM W 6.1 N/A N/A NO 153.0 None 855327T T T2bN0MX Negative none nf n 6.060s M W 9.1 N/A N/A NO 137.0 None 8629T T T1CN0MX Negative none nf n 6.050s M W 6.5 N/A N/A NO 163.0 None 863176T T T3bN0MX Negative none nf n8.0 60s M W 11.7 1.4 1.0 NO 151.0 ADT, CHEMO 8712362T T T2bN0MX Negativenone nf n 8.0 50s M W 10.4 N/A N/A NO 155.0 None 8713205T T T2bN0MXNegative slow nf y 10.0 60s M W 8.3 12.0 18.3 NO 161.0 NK 8741T TT2bN0MX Negative none nf n 6.0 60s M W 9.1 N/A N/A NO 151.0 None 8433T TT3bN0MX Negative none nf n 8.0 60s M W 9.6 N/A N/A NO 160.0 None 9122T TT1CN0MX Negative none nf n 7.0 50s M W 13.0 N/A N/A NO 164.0 None9210207T T T3bN0MX Negative slow nf y 8.0 60s M W 14.6 20.0 3.2 NO 105.0NK 9217293T T T3bN0MX Negative slow nf y 8.0 60s M W 7.8 20.0 16.9 NO132.0 NK 92SR293T T T2bN0MX Negative none nf n 6.0 50s M W 6.5 N/A N/ANO 155.0 None 9412443T T T3bN0MX Negative fast f y 8.0 50s M W 11.1 4.32.1 NO 78.0 ADT, CHEMO 9812033T T T2bN0MX Negative none nf n 6.0 50s M W7.9 N/A N/A NO 165.0 None 9814481T T T3bN0MX Negative slow nf y 9.0 60sM W 11.3 38.0 21.0 NO 160.0 NK 98TA- T T3bN0MX Negative none nf n 7.060s M W 13.2 N/A N/A NO 151.0 None 83782T 991199T T T3bN0MX Negativeslow nf y 8.0 50s M W 15.5 15.0 24.0 NO 151.0 ADT, CHEMO 9927086T TT2BN0MX Negative none nf n 6.0 50s M W 9.5 N/A N/A NO 158.0 None 994308TT T1cN0MX Negative none nf n 6.0 60s M W 8.3 N/A N/A NO 160.0 None995772T T T3bN0MX Negative none nf n 7.0 60s M W 8.7 N/A N/A NO 163.0None DB8237T T TbN0MX Negative slow nf y 6.0 70s M W 6.3 46.0 26.0 NO123.4 NK FB120T T T3aN0MX Negative slow nf y 7.0 60s M W 61.1 1.3 20.8NEGATIVE 94.9 NK FB174T T T3aN0MX Negative fast f y 7.0 60s M W 6.9 30.53.2 NEGATIVE 94.7 ADT, CHEMO, RT FB183T T T2cN0MX Negative slow nf y 7.060s M W 9.7 78.8 25.6 NO 99.1 NK FB238T T T3bN0MX Negative slow nf y 7.060s M W 15.9 41.0 30.0 NO 101.7 NK FB421T T T3aN0MX Negative fast f y7.0 60s M W 4.5 1.3 4.4 POSITIVE FOR 92.1 ADT BONE METASTASIS FB76T TT2cN0MX Negative none nf n 7.0 50s M W 6.5 N/A N/A not done 130.0 NoneFB94T T T2cN0MX Negative slow nf y 7.0 60s M W 5.1 48.6 15.2 NEGATIVE96.6 NK GB195T T T2cN0MX Negative slow nf y 7.0 60s M W 10.1 53.2 23.8NEGATIVE 65.2 RT GB368T T T3aN0MX Negative slow nf y 7.0 50s M W 5.570.0 15.0 not done 112.0 None GB400T T T3bN0MX Negative fast f y 7.0 60sM W 3.5 29.6 4.2 NEGATIVE 78.9 ADT, RT HB021T T T2bN0MX Negative fast fy 6.0 50s M W 5.9 24.2 4.0 NEGATIVE 80.1 ADT, RT HB033T T T2cN0MXNegative none nf n 7.0 50s M W 8.4 N/A N/A NO 87.0 None HB207T T T3bN0MXNegative fast f y 9.0 60s M W 6.3 5.5 0.6 POSITIVE FOR 74.7 ADT, BONECHEMO METASTASIS HB235T T T3bN1MX Negative slow nf y 9.0 60s M W 4.6 1.320.8 POSITIVE FOR 10.7 ADT, BONE CHEMO METASTASIS HB261T T T3aN0MXNegative none nf n 7.0 50s M W 5.4 N/A N/A NO 74.0 None HB303T T T2cN0MXNegative none nf n 7.0 60s M W 31.3 N/A N/A not done 102.0 None HB305T TT3bN0MX Negative fast f y 6.0 60s M W 10.1 1.4 3.9 NO 68.8 ADT, CHEMOHB322T T T2cN0MX Negative none nf n 7.0 60s M W 4.9 N/A N/A not done102.0 None HB327T T T2cN0MX Negative none nf n 8.0 50s M W 9.5 N/A N/Anot done 102.0 None HB340T T T2cN0MX Negative ND ND ND 7.0 60s M W 9.6N/A N/A not done 32.0 None HB346T T T3aN0MX Negative none nf n 7.0 60s MW 17.2 N/A N/A not done 102.0 None HB46T T T3bN0MX Negative slow nf y8.0 60s M W 4.7 20.1 15.3 NO 69.1 NK HB492T T T2cN0MX Negative slow nf y7.0 50s M W 7.4 82.0 25.0 negative 99.0 None HB504T T T3bN0MX Positivefast f y 8.0 50s M U 70.0 4.3 0.7 NEGATIVE 58.7 ADT, CHEMO HB526T TT3bN0MX Positive fast f y 6.0 60s M W 8.7 1.4 2.7 POSITIVE FOR 23.9 ADT,BONE CHEMO METASTASIS HB568T T T3bN0MX Negative fast f y 7.0 60s M W 4.422.4 4.2 NEGATIVE 68.2 ADT, RT HB591T T T3bN1MX Negative fast f y 7.060s M W 17.6 1.3 3.6 POSITIVE FOR 47.0 ADT, BONE AND CHEMO HEPATICMETASTASIS HB603T T T3aN1MX Negative slow nf y 7.0 60s M W 8.4 22.1 15.9NO 70.7 HB658T T T3bN0MX Negative none nf n 7.0 70s M W 20.6 N/A N/A notdone 97.0 None HB705T T T2cN0MX Negative none nf n 7.0 60s M W 9.8 N/AN/A not done 97.0 None HB951T T T3bN1MX Negative fast f y 7.0 60s M W23.1 15.9 4.0 POSITIVE FOR 47.0 ADT, BONE AND CHEMO HEPATIC METASTASISIB071T T T3aN0MX Negative fast f y 7.0 60s M W 2.6 4.3 1.6 POSITIVE FOR45.6 ADT, RT BONE METASTASIS IB110T T T2cN0MX Negative none nf n 8.0 60sM W 2.7 N/A N/A not done 94.0 None IB111T T T2cN0MX Negative none nf n7.0 60s M W 9.5 N/A N/A not done 94.0 None IB112T T T3aN0MX Negativeslow nf y 7.0 60s M W 4.7 55.8 30.6 NO 67.2 NK IB134T T T3bN0MX Negativenone nf n 9.0 70s M W 15.7 N/A N/A NO 77.0 None IB136T T T3bN1MXNegative fast f y 8.0 50s M W 19.6 1.8 2.2 POSITIVE FOR 69.2 ADT, BONECHEMO METASTASIS IB180T T T2cN0MX Negative none nf n 7.0 60s M W 3.0 N/AN/A not done 93.0 None IB273T T T2bN0MX Negative fast f y 7.0 50s M W4.3 10.6 4.0 NEGATIVE 60.8 RT IB289T T T2aN0MX Negative none nf n 7.060s M W 10.0 N/A N/A not done 91.0 None IB298T T T3bN0MX Negative slownf y 7.0 60s M W 5.3 34.3 20.4 NO 67.0 NK IB362T T T3bN0MX Negative slownf y 7.0 50s M W 18.9 4.6 16.0 NEGATIVE 65.2 RT IB378T T T3bN0MXNegative none nf n 7.0 60s M W 2.8 N/A N/A not done 90.0 None IB483T TT2bN0MX Negative fast f y 7.0 50s M W 5.2 1.4 1.7 NO 54.8 ADT, CHEMOJB154T T T3bN0MX Negative fast f y 8.0 50s M U 70.0 3.5 0.9 NEGATIVE58.7 ADT, CHEMO JB197T T T3bN0MX Positive fast f y 7.0 50s M W 11.2 1.48.85 SINGLE FOCUS 48.4 ADT, (death) OF INCREASED CHEMO ACTIVITY JB426T TT2cN0MX Negative fast f y 7.0 60s M W 5.7 17.4 2.3 NEGATIVE 50.9 ADT, RTJB770T T T2cN0MX Negative fast f y 8.0 60s M W 2.4 33.8 3.0 NEGATIVE33.9 RT KB170T T T3bN1MX Negative fast f y 7.0 70s M W 14.1 1.8 4.2POSITIVE FOR 37.2 ADT NODAL METASTASIS PR018ST T T3aN0MX Positive slownf y 7.0 60s M W 9.0 78.0 55.0 NO 140.2 PR053T T TURP Negative fast f yTURP 60s M W 182.5 1.0 0.2 bone metastasis 15.0 ADT, CHEMO PR079T TT3aN0MX Positive slow nf y 7.0 60s M W 5.1 95.3 17.3 NO 129.8 PR227T TT2cN0MX Negative none nf n 7.0 60s M W 4.5 N/A N/A not done 135.0 NonePR236T T T3bN0MX Negative fast f y 10.0 60s M W 9.9 1.3 3.9 POSITIVE FOR64.7 ADT, BLASTIC CHEMO METASTASIS PR300T T T3bN1MX Negative fast f y7.0 50s M W 20.3 71.5 3.9 NEGATIVE 98.5 NK PR303T T T3bN0MX Negativeslow nf y 6.0 70s M W 10.5 54.6 43.3 NO 79.7 NK PR306T T T3bN0MXPositive slow nf y 7.0 60s M W 11.5 16.4 52.9 NEGATIVE 109.1 RT PR310T TT3bN0MX Negative fast f y 7.0 60s M W 5.1 22.8 1.6 POSITIVE FOR 47.7ADT, BONE AND CHEMO, ILIAC RT METASTASIS PR375T T T3bN1MX Negative fastf y 7.0 50s M W 11.3 1.2 1.1 POSITIE FOR 114.9 ADT, BONE AND CHEMO,PELVIC RT METASTASIS PR434T T T3aN0MX Negative slow nf y 7.0 60s M W 6.472.8 30.8 NO 137.6 RT PR521T T T2bN0MX Negative slow nf y 7.0 50s M W6.4 79.2 15.5 NO 126.2 RT PR530T T T2cN0MX Negative ND ND ND 7.0 60s M W4.4 N/A N/A Not Done 25.0 None PR534T T T2bN0MX Negative none nf n 6.060s M W 8.4 N/A N/A not done 13.0 None PR536T T T2bN0MX Negative none nfn 7.0 50s M W 5.4 N/A N/A not done 136.0 None R10T T T3bN0MX Negativefast f y 8.0 60s M W 13.1 11.0 2.3 NO 74.0 ADT, CHEMO R13T T T3bN0MXNegative none nf n 7.0 60s M W 10.4 N/A N/A NO 157.0 None R16T T T2bN0MXNegative none nf n 7.0 50s M W 5.8 N/A N/A NO 159.0 None R18T T T2bN0MXNegative none nf n 7.0 50s M W 9.1 N/A N/A NO 163.0 None R19T T T3bN0MXNegative slow nf y 9.0 60s M W 13.8 2.0 1.1 NO 60.0 ADT, CHEMO R26T TT3aN0MX Negative none nf n 7.0 60s M W 7.7 N/A N/A NO 146.0 None R3T TT2bN0MX Negative none nf n 7.0 60s M W 7.1 N/A N/A NO 137.0 None R57T TT3bN0MX Negative none nf n 7.0 50s M W 8.8 N/A N/A NO 107.0 None R59T TT3bN0MX Negative none nf n 7.0 60s M W 9.8 N/A N/A NO 127.0 None R61T TT3bN0MX Negative none nf n 7.0 60s M W 12.5 N/A N/A NO 160.0 NoneSR9R57T T T2bN0MX Negative none nf n 7.0 60s M W 7.2 N/A N/A NO 161.0None TP08PP- T T3bN1MX Negative fast f y 9.0 50s M W 20.2 1.3 1.1POSITIVE FOR 17.0 ADT, S0721T BONE CHEMO METASTASIS TP08- T T3bN0MXNegative fast f y 7.0 60s M W 11.1 1.3 3.3 NEW LEFT 37.2 ADT S00530TEXTERNAL ILIAC LYMPH NODE; NO METASTASIS TP08- T T2cN0MX Negative fast fy 7.0 50s M W 4.3 1.9 3.6 POSITIVE FOR 30.6 RT S00542T BLASTIC ANDHEPATIC METASTASIS TP09- T T3bN1MX Negative fast f y 8.0 50s M W 4.9 4.61.2 NEW 27.1 ADT S0006T SCLEROTIC FOCUS @T12 TP09- T T3bN1MX Negativefast f y 7.0 50s M W 14.6 1.4 3.7 NEGATIVE 29.1 ADT S0420T TP09- TT4N1MX Negative fast f y 9.0 60s M W 55.0 29.3 1.9 not done 67.0 ADT,S0704T CHEMO TP09- T T3bN1MX Negative fast f y 10.0 50s M W 29.3 1.4 0.9POSITIVE FOR 15.5 ADT, S0721T BONE CHEMO METASTASIS TP10PP- T T3bN1MXNegative fast f y 7.0 50s M W 15.8 1.7 3.3 NEGATIVE 30.6 ADT S0420TTP10- T T3bN1MX Negative fast f y 10.0 50s M W 9.2 1.4 1.8 POSITIVE FOR149.6 ADT S0638T BONE METASTASIS TP10- T T3aN0MX Negative slow nf y 7.060s M W 4.1 43.8 40.0 NO 133.3 RT S093T TP11PP- T T3bN1MX Negative fastf y 9.0 50s M W 11.3 1.6 1.9 POSITIVE FOR 137.0 ADT S0638T BONEMETASTASIS TP12- T T3aN0MX Negative ND ND ND 8.0 70s M W 7.9 ND ND NotDone 23.0 None S0048T TP12- T T2cN0MX Negative ND ND ND 7.0 60s M W 13.6ND ND Not Done 23.0 None S0049T TP12- T T3aN1MX Negative ND ND ND 7.060s M W 10.7 ND ND Not Done 23.0 None S0102T TP12- T T3aN0MX Negative NDND ND 7.0 50s M W 4.2 ND ND Not Done 22.0 None S0191T TP12- T T2cN0MXNegative ND ND ND 7.0 50s M AA 7.3 ND ND Not Done 22.0 None S0194T TP12-T T2cN1MX Negative ND ND ND 7.0 60s M W 3.9 ND ND Not Done 22.0 NoneS0246T TP12- T T2aN1MX Negative fast f y 7.0 60s M W 13.8 1.4 0.3Bone/CT Scan(s) - 33.0 ADT S0337T negative TP12- T T3bN1MX Negative fastf y 9.0 60s M W 5.5 7.4 2.6 Not Done 33.0 ADT S0340T TP12- T T3aN1MXNegative ND ND ND 8.0 60s M W 6.0 ND ND Not Done 20.0 None S0456T TP12-T T3bN1MX Negative fast f y 8.0 50s M W 6.1 1.4 0.2 negative 22.0 ADTS0466T TP12- T T3aN1MX Negative fast f y 8.0 60s M W 20.3 1.5 0.8 notdone 19.0 ADT S0608T TP12- T T3bN1MX Negative fast f y 7.0 70s M W 3.31.4 2.0 not done 19.0 none S0624T TP12- T T3aN0MX Negative ND ND ND 7.050s M W 5.0 N/A N/A not done 17.0 none S0704T TP12- T T2cN0MX NegativeND ND ND 7.0 60s M W 5.4 ND ND Not Done 16.0 None S0723T TP12- T T3bN0MXNegative fast f y 9.0 50s M W 25.0 1.6 0.5 Bone/CT Scan(s) - 30.0 NoneS0740T negative TP12- T T3aN0MX Negative ND ND ND 7.0 50s M W 5.0 ND NDNot Done 17.0 None S0765T TP12- T T3aN0MX Negative ND ND ND 7.0 40s M W9.0 ND ND Not Done 19.0 None S0770T TP12- T T3bN1MX Negative fast f y7.0 60s M W 4.5 1.3 0.6 not done 30.0 ADT S0786T TP12- T T3bN1MXNegative ND ND ND 7.0 60s M W 10.6 ND ND Not Done 17.0 None S0789T TP12-T T3aN0MX Negative Fast f y 7.0 60s M W 24.2 11.7 3.7 Not Done 29.0 NoneS0790T TP12- T T2cN0MX Negative ND ND ND 7.0 50s M W 2.4 ND ND Not Done17.0 None S0795T TP12- T T3aN0MX Negative ND ND ND 7.0 50s M W 6.4 ND NDCT Scan(s) - 17.0 None S0799T negative TP12- T T2cNXMX Negative ND ND ND7.0 60s M W unknown ND ND Not Done 17.0 None S0803T TP12- T T2cN0MXNegative ND ND ND 7.0 50s M W 4.0 ND ND Not Done 22.0 None S0805T TP12-T T3aN0MX Negative ND ND ND 7.0 50s M W 6.5 ND ND Not Done 17.0 NoneS0816T TP12- T T3aNXMX Negative ND ND ND 7.0 60s M W 5.0 ND ND Not Done16.0 None S0915T TP12- T T3aN0MX Negative ND ND ND 7.0 60s M W 5.0 N/AN/A not done 16.0 none S0916T TP12- T T3bN1MX Negative fast f y 9.0 70sM W 6.8 0.9 2.2 CT Scan(s) - 28.0 ADT S0918T negative TP12- T T3aN0MXNegative ND ND ND 7.0 60s M W 5.3 ND ND Not Done 16.0 None S0928T TP12-T T3aN1MX Negative fast f y 9.0 50s M W 10.3 9.1 3.1 Not Done 28.0 NoneS0943T TP12- T T3bN0MX Negative fast f y 7.0 60s M W 15.7 1.5 0.4 notdone 16.0 None S0954T TP12- T T3aN0MX Negative ND ND ND 7.0 50s M W 12.2ND ND Not Done 16.0 None S0966T TP12- T T3aN0MX Negative ND ND ND 7.060s M W 6.0 N/A N/A Not Done 14.0 None S0967T TP12- T T3bN0MX NegativeND ND ND 7.0 60s M W 56.4 ND ND Not Done 16.0 None S0981T TP12- TT3aN0MX Negative ND ND ND 7.0 60s M W 16.6 ND ND Not Done 13.0 NoneS0988T TP12- T T3aN0MX Negative ND ND ND 7.0 60s M W 9.2 ND ND Not Done141.0 None S1032T TP12- T T3aN0MX Negative fast f y 8.0 60s M W 10.6 1.30.4 not done 15.0 none S1059T TP12- T T2cN0MX Negative ND ND ND 7.0 60sM W 18.5 ND ND Not Done 15.0 None S1189T TP12- T T2cN0MX Negative ND NDND 7.0 70s M W 5.0 ND ND Not Done 14.0 None S1197T TP12- T T2cN0MXNegative ND ND ND 7.0 60s M W 4.9 ND ND Not Done 16.0 None S1224T TP13-T T3aN0MX Negative fast f y 8.0 60s M W 22.0 1.5 0.2 NO 12.0 None S0043TTP13- T T3bN1MX Negative fast f y 8.0 70s M W 21.5 1.6 1.1 NO 12.0 NoneS0109T TP13- T T3bN1MX Negative fast f y 8.0 60s M W 6.8 2.1 0.5 NO 11.0ADT S0248T TP13- T T3aN0MX Negative fast f y 7.0 60s M W 3.6 7.8 2.0 NO9.0 None S0314T TP13- T T3aN0MX Negative fast f y 9.0 50s M W 29.9 1.91.9 NO 7.0 None S0456T TP13- T T3bN1MX Negative fast f y 9.0 50s M W10.0 1.1 0.3 NO 7.0 None S0464T f-PSADT ≤4 months; nf-PSADT ≥15 months;y—yes; n—no; ADT—androgen deprivation therapy; RT—radiation therapy;Chemo—chemotherapy; ND—not determined.

TABLE 8 Clinical and pathological characteristics of 30 cases ofprostate cancer from Stanford cohort. Preop Pre- Path Months Sample AgeEthnicity RX PSA T N M Grade Angio Margins followup PC 19T 50s CaucasianNone 4.42 T3a N1 M0 4 + 5 Yes Negative 116.2 PC 60s Caucasian None 42 T4N0 M0 3 + 4 Unknown Positive 22.86666667 252T PC 50s African None 4.53T2b N0 M0 4 + 4 Unknown Negative 20.76666667 265T American PC 60sCaucasian None 5.12 T2b N0 M0 4 + 3 Unknown Negative 89.3 452T PC 50sAfrican Horm 4.01 T3b N0 M0 4 + 3 Unknown Negative 82.7 366T American PC60s Caucasian None 10.7 T2b N0 M0 3 + 4 No Negative 73 538T PC 47T 50sCaucasian None 9.92 T2b N0 M0 3 + 4 Unknown Negative 64.66666667 PC 97T50s Caucasian None 4.1 T2b N0 M0 4 + 3 Unknown Negative 117 PC 50sCaucasian None 10.76 T3b N1 M0 4 + 4 Yes Negative 68.8 370T PC 60sCaucasian None 15.44 T2b N1 M0 3 + 4 Unknown Negative 40.06666667 405TPC 60s Caucasian None 7.1 T3b N0 M0 3 + 4 Unknown Negative 72 448T PC60s Caucasian None 5.91 T2b N0 M0 3 + 4 Yes Negative 71.6 485T PC 50sCaucasian None 4.68 T2b N0 M0 3 + 3 Unknown Negative 50.66666667 498T PC40s Caucasian None 4.8 T2b N0 M0 3 + 3 Unknown Negative 47.6 551T PC 60sCaucasian None 2.38 T2b N0 M0 3 + 4 Unknown Negative 41.43333333 494T PC70s African None 3.2 T2b N0 M0 3 + 3 Unknown Negative 48.3 629T AmericanPC 60s Caucasian None 7.16 T2b N0 M0 3 + 4 No Negative 43.8 643T PC 60sCaucasian None 4.9 T2b N0 M0 3 + 4 Unknown Negative 49 646T PC 60s AsianNone 4.64 T2b N0 M0 3 + 4 Unknown Negative 52.83333333 473T PC 70sCaucasian None 6.8 T2b N0 M0 3 + 4 Unknown Negative 47.86666667 470T PC70s Caucasian None 2.84 T2b N0 M0 3 + 3 Unknown Negative 45.9 482T PC15T 40s Caucasian None 5.12 T2b N0 M0 3 + 3 Unknown Negative 118 PC 60sCaucasian None 3.93 T2b N0 M0 4 + 3 Unknown Negative 74.6 501T PC 60sCaucasian None 3.9 T2b N0 M0 3 + 4 Unknown Positive 105.5 274T PC 60sCaucasian None 10.77 T2b N0 M0 3 + 3 Unknown Negative 61.96666667 343TPC 40s Caucasian None 8.9 T2b N0 M0 3 + 4 Unknown Negative 61.3 599T PC45T 50s Caucasian None 6.58 T2b N0 M0 3 + 4 No Negative 118.1 PC 86T 60sCaucasian None 2.1 T2b N0 M0 3 + 4 Unknown Negative 105.6 PC 99T 70sHispanic None 6.26 T2b N0 M0 3 + 4 Unknown Negative 120.6 PC 85T 40sCaucasian None 4.8 T2a N0 M0 3 + 4 Unknown Positive 98 Months to RelapseRelapse Sample Recurrence recurrent PSADT Relapse fast simple PC 19TBiochemical 19.13333333 4.11 fast f y PC Biochemical 10.2 3.85 fast f y252T PC Biochemical 2.77 3.89 fast f y 265T PC Biochemical 19.17 4.32fast f y 452T PC Biochemical 12.33 9.04 Intermediate nf y 366T PCBiochemical 24.86666667 8.55 Intermediate nf y 538T PC 47T Biochemical37.6 98.58 slow nf y PC 97T Biochemical 61.13333333 >20 slow nf y PCBiochemical 15.83 21.89 slow nf y 370T PC Biochemical 2.5 >20 slow nf y405T PC Biochemical 35.63 >20 slow nf y 448T PC Biochemical 49.7 20.69slow nf y 485T PC None ND n/a ND ND ND 498T PC None ND n/a ND ND ND 551TPC None ND n/a ND ND ND 494T PC None ND n/a ND ND ND 629T PC None ND n/aND ND ND 643T PC None ND n/a ND ND ND 646T PC None ND n/a ND ND ND 473TPC None ND n/a ND ND ND 470T PC None ND n/a ND ND ND 482T PC 15TNone >60 n/a none nf n PC None >60 n/a none nf n 501T PC None >60 n/anone nf n 274T PC None >60 n/a none nf n 343T PC None >60 n/a none nf n599T PC 45T None >60 n/a none nf n PC 86T None >60 n/a none nf n PC 99TNone >60 n/a none nf n PC 85T None >60 n/a none nf n f-PSADT ≤4 months;nf-PSADT ≥5 months; y—yes; n—no; ADT—androgen deprivation therapy;RT—radiation therapy Chemo-chemotherapy; ND—not determined.

TABLE 9 Clinical and pathological characteristics of 36 cases ofprostate cancer from Wisconsin cohort. Pre- Sample operational PSA IDAge Stage Margin PSA Grade recurrence W1 60s T1C +, and lymph node 123 + 3 yes W2 50s T1C − 4.5 3 + 4 no W3 50s T3a + 2.9 3 + 4 yes W4 70sT3a + 5 3 + 4 no W5 50s T2A + 5.1 3 + 4 yes W6 60s T2A +, and lymph node4.13 4 + 5 yes W7 60s T1C − 5.2 3 + 3 yes W8 40s T1C − 7 4 + 4 no W9 60sT1C − 4.95 3 + 4 yes W10 40s T1C +, and lymph node 42 3 + 4 yes W11 40sunknown + 5 4 + 3 yes W12 60s D0 − 6.3 4 + 5 yes W13 60s unknown − 4.33 + 4 yes W14 50s T2B − 2.5 3 + 3 no W15 70s T2B − 7.9 4 + 3 yes W16 60sT3A + 4.2 3 + 4 no W17 60s T2C + 5 3 + 4 no W18 60s T2C + 5.6 3 + 4 yesW19 60s T2C − unknown 4 + 3 no W20 60s T2C + 4.47 3 + 4 no W21 60s T2A −4 3 + 3 no W22 60s T3B + 6.7 3 + 4 yes W23 50s T2C − 5.7 3 + 4 no W2450s T3A − 5 3 + 4 no W25 50s T2C − 5.4 3 + 4 no W26 60s T2C − 4.6 3 + 4no W27 50s T2C − 4.1 3 + 3 no W28 unknown unknown unknown unknown 4 + 4ND W29 60s T2C + 4.6 3 + 4 no W30 60s unknown unknown unknown 5 + 5 noW31 60s T2c − 4 4 + 5 Yes W32 40s T3b + 27 4 + 5 Yes W33 50s unknownunknown unknown 4 + 4 Yes W34 50s T3b + 3.7 4 + 5 Yes W35 unknownunknown unknown unknown 4 + 5 ND W36 50s unknown unknown unknown 4 + 4ND

TABLE 10 The status of 8 fusion genes predicting prostate cancerrecurrence on 90 training cohort from UPMC*. Number of fusion accuracysensitivity specificity Youden Inex Panel of 8 fusion transcripts 10.567 0.19 1 0.19 2 0.644 0.33 1 0.33 3 0.622 0.33 0.95 0.29 4 0.6220.33 0.95 0.29 5 0.644 0.38 0.95 0.33 6 0.711 0.5 0.95 0.45 7 0.689 0.50.91 0.40 8 0.711 0.58 0.89 0.47 Panel of 8 fusion transcripts plusTMPRSS2-ERG 1 0.589 0.42 0.79 0.20 2 0.622 0.48 0.79 0.27 3 0.6 0.480.74 0.22 4 0.6 0.48 0.74 0.22 5 0.611 0.5 0.74 0.24 6 0.656 0.58 0.740.32 7 0.633 0.58 0.69 0.27 8 0.656 0.63 0.69 0.32 *Using any fusiontranscript as cutoff.

TABLE 11 The status of 8 fusion genes with or without TMPRSS2- ERGpredicting prostate cancer recurrence*. Cohort accuracy sensitivityspecificity 8 fusion transcript UPMC training 0.711 0.58 0.89 UPMCtesting 0.705 0.51 0.95 Wisconsin 0.8 0.63 1 Stanford 0.762 0.67 0.89Combined testing'' 0.734 0.56 0.951 8 fusion transcript plus TMPRSS2-ERGUPMC training 0.656 0.63 0.69 UPMC testing 0.681 0.67 0.69 Wisconsin0.767 0.69 0.86 Stanford 0.762 0.83 0.67 Combined testing'' 0.712 0.700.73 *Using any fusion transcript as cutoff; **-Combining UPMC testing,Stanford and Wisconsin data set.

TABLE 12 Association of fusion transcript with clinical/pathologicalparameters. P value PSA Tumor Lymph Fusion gene Gleason (pre-operation)stage node Nomogram TMEM135-CCDC67 0.59 0.98 0.432 0.082 0.21KDM4B-AC011523.2 0.64 0.726 0.688 0.588 0.588 MAN2A1-FER 0.781 0.7210.679 0.140 1.07E−03 CCNH-C5orf30 0.14 0.313 0.254 0.059 0.156TRMT11-GRIK2 0.012 0.227 5.38E−04 0.013 8.56E−03 SLC45A2-AMACR 0.5660.441 0.022 0.181 0.015 MTOR-TP53BP1 0.993 0.57 0.731 1 0.775LRRC59-FLJ60017 0.877 0.034 0.226 0.206 0.188 At least one 0.064 0.1383.852e−3  4.77e−3 2.86E−04 TMPRSS2-ERG 0.869 0.306 0.642 0.042 0.325

TABLE 13 Gleason score prediction of recurrent status of 90 samples ofUPMC training Cohort. Score accuracy sensitivity specificity YoudenIndex 6 0.5333333 1 0 0 7 0.6111111 0.95833333 0.2142857 0.17261905 80.6111111 0.39583333 0.8571429 0.25297619 9 0.5111111 0.166666670.9047619 0.07142857 10 0.4666667 0.02083333 0.9761905 −0.00297619

TABLE 14 Gleason score prediction of recurrent status of 229^(|) samplesof training and testing cohorts from UPMC, Stanford and Wisconsin*.Cohort accuracy sensitivity specificity Gleason alone UPMC training0.611 0.40 0.86 UPMC testing 0.602 0.41 0.85 Wisconsin 0.6 0.31 0.93Stanford 0.571 0.25 1 Combined testing'' 0.597 0.37 0.89 Gleason plus 8fusion transcripts⁺ UPMC training 0.722 0.65 0.81 UPMC testing 0.7390.59 0.92 Wisconsin 0.9 0.81 1 Stanford 0.762 0.67 0.89 Combinedtesting'' 0.777 0.65 0.94 Gleason plus 8 fusion transcripts plusTMPRSS2-ERG' UPMC training 0.644 0.73 0.55 UPMC testing 0.705 0.80 0.59Wisconsin 0.833 0.88 0.79 Stanford 0.762 0.83 0.67 Combined testing''0.741 0.82 0.65 *Using Gleason >= 8 as cutoff; ⁺Using Gleason >= 8 orpresence of any fusion transcript as cutoff; ^(|)Using <88 or presenceof any fusion transcript or TMPRSS2-ERG as cutoff; **-Combining UPMCtesting, Stanford and Wisconsin data set; ^(|)Gleason score is notgraded in one sample and not included in the analysis.

TABLE 15 Nomogram prediction of recurrent status of 90 samples of UPMCtraining Cohort. Probability* accuracy sensitivity specificity Youdenindex 0 0.4666667 0 1 0 1 0.4666667 0 1 0 2 0.4666667 0 1 0 3 0.46666670 1 0 4 0.4666667 0 1 0 5 0.4666667 0 1 0 6 0.4666667 0 1 0 7 0.46666670 1 0 8 0.4666667 0 1 0 9 0.4666667 0 1 0 10 0.4666667 0 1 0 110.4666667 0 1 0 12 0.4666667 0 1 0 13 0.4777778 0.02083333 1 0.0208333314 0.4777778 0.02083333 1 0.02083333 15 0.4777778 0.02083333 10.02083333 16 0.4777778 0.02083333 1 0.02033333 17 0.4777778 0.020833331 0.02083333 18 0.4777778 0.02083333 1 0.02083333 19 0.48888890.04166667 1 0.04166667 20 0.4888889 0.04166667 1 0.04166667 210.4888889 0.04166667 1 0.04166667 22 0.4888889 0.04166667 1 0.0416666723 0.4888889 0.04166667 1 0.04166667 24 0.4888889 0.04166667 10.04166667 25 0.5 0.0625 1 0.0625 26 0.5 0.0625 1 0.0625 27 0.51111110.08333333 1 0.08333333 28 0.5111111 0.08333333 1 0.08333333 290.5333333 0.125 1 0.125 30 0.5222222 0.125 0.97619048 0.10119048 310.5222222 0.125 0.97619048 0.10119048 32 0.5222222 0.125 0.976190480.10119048 33 0.5333333 0.14583333 0.97619048 0.12202381 34 0.54444440.16666667 0.97619048 0.14285714 35 0.5444444 0.16666667 0.976190480.14285714 36 0.5444444 0.16666667 0.97619048 0.14285714 37 0.54444440.16666667 0.97619048 0.14285714 38 0.5555556 0.1875 0.976190480.16369048 39 0.5555556 0.1875 0.97619048 0.16369048 40 0.5555556 0.18750.97619048 0.16369048 41 0.5555556 0.1875 0.97619048 0.16369048 420.5555556 0.1875 0.97619048 0.16369048 43 0.5777778 0.229166670.97619048 0.20535714 44 0.5888889 0.25 0.97619048 0.22619048 450.5888889 0.25 0.97619048 0.22619048 46 0.5888889 0.25 0.976190480.22619048 47 0.6 0.27083333 0.97619048 0.24702381 48 0.6 0.270333330.97619048 0.24702381 49 0.6 0.27083333 0.97619048 0.24702381 500.6111111 0.29166667 0.97619048 0.26785714 51 0.6111111 0.291666670.97619048 0.26785714 52 0.6111111 0.29166667 0.97619048 0.26785714 530.6222222 0.3125 0.97619048 0.28869048 54 0.6222222 0.3125 0.976190480.28869048 55 0.6222222 0.3125 0.97619048 0.28869048 56 0.6222222 0.31250.97619048 0.28869048 57 0.6333333 0.33333333 0.97619048 0.30952381 580.6444444 0.35416667 0.97619048 0.33035714 59 0.6444444 0.354166670.97619048 0.33035714 60 0.6555556 0.375 0.97619048 0.35119048 610.6555556 0.375 0.97619048 0.35119048 62 0.6555556 0.375 0.976190480.35119048 63 0.6444444 0.375 0.95238095 0.32738095 64 0.6333333 0.3750.92857143 0.30357143 65 0.6333333 0.375 0.92857143 0.30357143 660.6444444 0.39583333 0.92857143 0.32440476 67 0.6555556 0.416666670.92857143 0.3452381 68 0.6555556 0.41666667 0.92857143 0.3452381 690.6555556 0.41666667 0.92857143 0.3452381 70 0.6777778 0.458333330.92857143 0.38690476 71 0.6777778 0.47916667 0.9047619 0.38392857 720.6777778 0.5 0.88095238 0.38095238 73 0.6888889 0.52083333 0.880952380.40178571 74 0.6888889 0.52083333 0.88095238 0.40178571 75 0.68888890.52083333 0.88095238 0.40178571 76 0.6838889 0.52083333 0.880952380.40178571 77 0.7 0.54166667 0.88095238 0.42261905 78 0.7 0.541666670.88095238 0.42261905 79 0.7 0.54166667 0.88095238 0.42261905 800.7111111 0.5625 0.88095238 0.44345238 81 0.7111111 0.5625 0.880952380.44345238 82 0.7111111 0.58333333 0.85714286 0.44047619 83 0.70.58333333 0.83333333 0.41666667 84 0.7 0.58333333 0.83333333 0.4166666785 0.7111111 0.60416667 0.83333333 0.4375 86 0.7333333 0.645833330.83333333 0.47916667 87 0.7444444 0.66666667 0.83333333 0.5 880.7555556 0.6875 0.83333333 0.52083333 89 0.7333333 0.708333330.76190476 0.4702381 90 0.7222222 0.70833333 0.73809524 0.44642857 910.7111111 0.72916667 0.69047619 0.41964286 92 0.7 0.75 0.642857140.39285714 93 0.7111111 0.83333333 0.57142857 0.4047619 94 0.67777780.85416667 0.47619048 0.33035714 95 0.6888889 0.875 0.476190480.35119048 96 0.6777778 0.875 0.45238095 0.32738095 97 0.62222220.95833333 0.23809524 0.19642857 98 0.5444444 1 0.02380952 0.02380952 990.5333333 1 0 0 100 0.5333333 1 0 0 *Probability of PSA free survivalfor 5 years

TABLE 16 Nomogram prediction of recurrent status of 229^(|) samples oftraining and testing cohorts from UPMC, Stanford and Wisconsin. Cohortaccuracy sensitivity specificity Nomogram alone* UPMC training 0.7560.69 0.83 UPMC testing 0.75 0.80 0.69 Wisconsin 0.6 0.31 0.93 Stanford0.619 0.33 1 Combined testing'' 0.691 0.57 0.84 Nomogram plus 8 fusiontranscripts⁺ UPMC training 0.778 0.69 0.88 UPMC testing 0.807 0.76 0.87Wisconsin 0.833 0.69 1 Stanford 0.81 0.75 0.89 Combined testing'' 0.8130.74 0.90 Nomogram plus 8 fusion transcripts plus TMPRSS2-ERG' UPMCtraining 0.656 0.63 0.69 UPMC testing 0.681 0.67 0.69 Wisconsin 0.7670.69 0.86 Stanford 0.762 0.83 0.67 Combined testing'' 0.719 0.62 0.84*Using <88 as cutoff. ⁺Using <88 or any fusion transcript as cutoff;^(|)Using <88 or any fusion transcript or TMPRSS2-ERG as cutoff;**-Combining UPMC testing, Stanford and Wisconsin data set; ^(|)Gleasonscore is not graded in one sample and not included in the analysis.

TABLE 17 Putative fusion transcripts from benign prostate of healthyorgan donors. Fusion gene 1 Fusion_gene2 read pairs Validation StatusSORBS1 RP11-476E15.3 25 AHCY RP11-292F22.3 25 DCUN1D3 ERI2 12 MACF1KIAA0754 11 C10orf68 CCDC7 11 RT-PCR and sequencing RP11-166D19.1 BLID 7ASS1 ASS1P9 6 BACH1 BACH1-IT1 6 RT-PCR MPDZ RP11-272P10.2 5 LIG3RP5-837J1.2 4 ACAD8 GLB1L3 4 RT-PCR IGSF9B RP11-259P6.1 3 EYA1RP11-1102P16.1 3 TTC33 PRKAA1 3 RT-PCR DNAH1 GLYCTK 3 PSPC1 ZMYM5 3HSP90AB3P RP11-759L5.2 3 LSAMP RP11-384F7.2 3 RNF4 FAM193A 81 RT-PCRAHCY RP11-292F22.3 9 LSAMP RP11-384F7.2 8 CBLL1 AC002467.7 4 FNBP4 Y_RNA4 TBCE RP11-293G6_—A.2 4 TRIM58 RP11-63487.4 4 DCUN1D3 ERI2 4 PHPT1MAMDC4 3 TRIP6 SLC12A9 3 NAT14 ZNF628 3 TLL2 RP11-35J23.5 3 UFSP2 Y_RNA3 TSPAN33 Y_RNA 3 CADM3 DARC 3 KIF27 KP11-213G2.3 3 RABL6 KIAA1984 3ZNF615 ZNF350 3 ZYG11A RP4-631H13.2 3 RP11-522L3.6 MTND4P32 3 MTND3P10AC012363.10 3 RP11-464F9.1 BMS1P4 3 RNF4 FAM193A 14 RT-PCR GBP3 Y_RNA 3NACA PRIM1 1 AHCY RP11-292F22.3 3 GBP3 Y_RNA 3 HARS2 ZMAT2 2 RT-PCR andsequencing EED C11orf73 1 RT-PCR CNPY3 RP3-475N16.1 1 RT-PCR RN7SL2Metazoa_SRP 1 SLC16A8 BAIAP2L2 2 RT-PCR KLK4 KLKP1 2 RT-PCR andsequencing ZNF137P ZNF701 1 RT-PCR AZGP1 GJC3 1 RT-PCR USP7RP11-252I13.1 1 TRRAP AC004893.11 1 C6orf47 BAG6 1 RT-PCR TTTY15 USP9Y 9AC005077.12 LINC00174 2 ADCK4 NUMBL 2 ZNF606 C19orf18 2 SLC45A3 ELK4 3RT-PCR and sequencing

6.6. References

-   1. Jemal A, Bray F, Center M M, Ferlay J, Ward E, Forman D. Global    cancer statistics. C A Cancer J Clin. Feb. 4 2012.-   2. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA    Cancer J Clin. January-February 2012; 62(1):10-29.-   3. Li H, Durbin R. Fast and accurate short read alignment with    Burrows-Wheeler transform. Bioinformatics. Jul. 15, 2009;    25(14):1754-1760.-   4. Trapnell C, Roberts A, Goff L, et al. Differential gene and    transcript expression analysis of RNA-seq experiments with TopHat    and Cufflinks. Nat Protoc. March 2012; 7(3):562-578.-   5. Trapnell C, Williams B A, Pertea G, et al. Transcript assembly    and quantification by RNA-Seq reveals unannotated transcripts and    isoform switching during cell differentiation. Nat Biotechnol. May    2010; 28(5):511-515.-   6. Trapnell C, Pachter L, Salzberg S L. TopHat: discovering splice    junctions with RNA-Seq. Bioinformatics. May 1, 2009;    25(9):1105-1111.-   7. Edgren H, Murumagi A, Kangaspeska S, et al. Identification of    fusion genes in breast cancer by paired-end RNA-sequencing. Genome    Biol. 12(1):R6.-   8. Wei Zeng C-W F, Stefan Muller Arisona, Huamin Qu. Visualizing    Interchange Patterns in Massive Movement Data. Computer Graphics    Forum. 2013(32):271-280.-   9. Luo J H, Yu Y P, Cieply K, et al. Gene expression analysis of    prostate cancers. Mol Carcinog. January 2002; 33(1):25-35.-   10. Yu Y P, Landsittel D, Jing L, et al. Gene expression alterations    in prostate cancer predicting tumor aggression and preceding    development of malignancy. J Clin Oncol. Jul. 15, 2004;    22(14):2790-2799.-   11. Ren B, Yu G, Tseng G C, et al. MCM7 amplification and    overexpression are associated with prostate cancer progression.    Oncogene. Feb. 16, 2006; 25(7):1090-1098.-   12. Yu Y P, Yu G, Tseng G, et al. Glutathione peroxidase 3, deleted    or methylated in prostate cancer, suppresses prostate cancer growth    and metastasis. Cancer Res. Sep. 1, 2007; 67(17):8043-8050.-   13. Tomlins S A, Rhodes D R, Perner S, et al. Recurrent fusion of    TMPRSS2 and ETS transcription factor genes in prostate cancer.    Science. Oct. 28, 2005; 310(5748):644-648.-   14. Berger M F, Lawrence M S, Demichelis F, et al. The genomic    complexity of primary human prostate cancer. Nature. February 10;    470(7333):214-220.-   15. Baca S C, Prandi D, Lawrence M S, et al. Punctuated evolution of    prostate cancer genomes. Cell. April 25; 153(3):666-677.-   16. Freedland S J, Humphreys E B, Mangold L A, et al. Death in    patients with recurrent prostate cancer after radical prostatectomy:    prostate-specific antigen doubling time subgroups and their    associated contributions to all-cause mortality. J Clin Oncol. May    1, 2007; 25(13):1765-1771.-   17. Antonarakis E S, Zahurak M L, Lin J, Keizman D, Carducci M A,    Eisenberger M A. Changes in PSA kinetics predict metastasis-free    survival in men with PSA-recurrent prostate cancer treated with    nonhormonal agents: combined analysis of 4 phase II trials. Cancer.    March 15; 118(6):1533-1542.-   18. Sinclair P B, Sorour A, Martineau M, et al. A fluorescence in    situ hybridization map of 6q deletions in acute lymphocytic    leukemia: identification and analysis of a candidate tumor    suppressor gene. Cancer Res. Jun. 15, 2004; 64(12):4089-4098.-   19. Misago M, Liao Y F, Kudo S, et al. Molecular cloning and    expression of cDNAs encoding human alpha-mannosidase II and a    previously unrecognized alpha-mannosidase IIx isozyme. Proc Natl    Acad Sci USA. Dec. 5, 1995; 92(25):11766-11770.-   20. Krolewski J J, Lee R, Eddy R, Shows T B, Dalla-Favera R.    Identification and chromosomal mapping of new human tyrosine kinase    genes. Oncogene. March 1990; 5(3):277-282.-   21. Prakash T, Sharma V K, Adati N, Ozawa R, Kumar N, Nishida Y,    Fujikake T, Takeda T, Taylor T D: Expression of conjoined genes:    another mechanism for gene regulation in eukaryotes, PLoS One 2010,    5:e13284.-   22. Youden W J: Index for rating diagnostic tests, Cancer 1950,    3:32-35.-   23. Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J C,    Muller M: pROC: an open-source package for R and S+ to analyze and    compare ROC curves, BMC Bioinformatics 12:77.-   24. Towns W L, Begley T J: Transfer RNA methytransferases and their    corresponding modifications in budding yeast and humans: activities,    predications, and potential roles in human health, DNA Cell Biol    2012, 31:434-454.-   25. Misago M, Liao Y F, Kudo S, Eto S, Mattei M G, Moremen K W,    Fukuda M N: Molecular cloning and expression of cDNAs encoding human    alpha-mannosidase II and a previously unrecognized alphamannosidase    IIx isozyme, Proc Natl Acad Sci USA 1995, 92:11766-11770.-   26. Fisher R P, Morgan D O: A novel cyclin associates with MO15/CDK7    to form the CDK-activating kinase, Cell 1994, 78:713-724.-   27. Yang H, Rudge D G, Koos J D, Vaidialingam B, Yang H J, Pavletich    N P: mTOR kinase structure, mechanism and regulation, Nature 2013,    497:217-223.-   28. Wang H, Luo K, Tan L Z, Ren B G, Gu L Q, Michalopoulos G, Luo J    H, Yu Y P: p53-induced gene 3 mediates cell death induced by    glutathione peroxidase 3, J Biol Chem 2012, 287:16890-16902.-   29. Zhen Y, Sorensen V, Skjerpen C S, Haugsten E M, Jin Y, Walchli    S, Olsnes S, Wiedlocha A: Nuclear import of exogenous FGF1 requires    the E R-protein LRRC59 and the importins Kpnalpha1 and Kpnbeta1,    Traffic 2012, 13:650-664.-   30. Yang J, Jubb A M, Pike L, Buffa F M, Turley H, Baban D, Leek R,    Gatter K C, Ragoussis J, Harris A L: The histone demethylase JMJD2B    is regulated by estrogen receptor alpha and hypoxia, and is a key    mediator of estrogen induced growth, Cancer Res 70:6456-6466.-   31. Savolainen K, Kotti T J, Schmitz W, Savolainen T I, Sormunen R    T, Ilves M, Vainio S J, Conzelmann E, Hiltunen J K: A mouse model    for alpha-methylacyl-CoA racemase deficiency: adjustment of bile    acid synthesis and intolerance to dietary methyl-branched lipids,    Hum Mol Genet 2004, 13:955-965.

7. EXAMPLE 2: PTEN-NOLC1 FUSION GENES

Transcriptome sequencing was performed on 15 samples of prostate cancerfrom patients who experienced prostate cancer recurrence after radicalprostatectomy. One of the candidate gene fusion transcripts isPTEN-NOLC1. To validate the fusion transcript, RT-PCRs using primersspecific for PTEN-NOLC1 were performed on the prostate cancer samplethat was positive for the fusion transcript, using the followingprimers: 5′-GCATTTGCAGTATAGAGCGTGC3′ (SEQ ID NO:28)/5′GTCTAAGAGGGAAGAGGCATTG3′ (SEQ ID NO: 29), under the followingconditions: 94° C. for 5′, then 30 cycles of 94° C. for 10 seconds, 61°C. for 1 min and 72° C. for 3 min, followed by 10 min at 72° C. forextension. A 158 bp PCR product was generated. The PCR product wassubsequently sequenced. PTEN-NOLC1 fusion transcript was confirmed (FIG.13A). To investigate the mechanism of PTEN-NOLC1 fusion transcript,Fluorescence In Situ Hybridizations (FISH) were performed using probescorresponding to 5′-end of PTEN genome (RP11-124B18) and 3′-end of NOLC1genome (CTD-3082D22), respectively. In normal prostate epithelial cells,these 2 probes were hybridized to distinct separate locations in thegenome due to more than 14 megabase separation of these 2 genes (FIG.13B). In contrast, these two signals appeared to merge to generate anoverlapped signal in prostate cancer genome from a sample that ispositive for PTEN-NOLC1 fusion transcript. Interestingly, non-fusionPTEN was virtually undetectable in this prostate cancer sample,suggesting that PTEN-NOLC1 fusion was accompanied with PTEN deletion inanother allele. These results suggest that genome rearrangement is theunderlying mechanism for PTEN-NOLC1 transcription. To investigate theclinical significance of PTEN-NOLC1 fusion, 215 prostate cancer sampleswere analyzed for PTEN-NOLC1 expression. Over 14% (31/215) prostatecancer samples were found to express PTEN-NOLC1 (FIG. 13C). Among thepositive samples, 77% (24/31, p=0.03) patients experienced prostatecancer recurrence. This indicates that PTEN-NOLC1 fusion is associatedwith poor clinical outcome. Interestingly, our analysis of lungadenocarcinoma, Glioblastoma multiforme, and hepatocellular carcinomaindicates that significant number of these cancers are also positive forPTEN-NOLC1 fusion: 35/38 glioblastoma multiformis, 3/20 hepatocellularcarcinoma and 29/40 lung adenocarcinoma. These results suggest thatPTEN-NOLC1 fusion may have broad implication for cancer development.

Expression of Pten-NOLC1 in NIH3T3 and PC3 Cells Increased Cell Growth.

To investigate whether PTEN-NOLC1 has pro-growth activity, we ligatedPTEN-NOLC1 cDNA into pCDNA-FLAG vector to create pCDNA4-PTEN-NOLC1-FLAG.Subsequently, we transfected NIH3T3 and PC3 cells (a human prostatecancer cell line) with pCDNA4-PTEN-NOLC1-FLAG/pCDNA6. As shown in FIG.27B, induction of NIH3T3 and PC3 cells produces 10.3 (p<0.01) and 3.1fold (p<0.01) increase of cell growth, respectively. These wereaccompanied with 2.3 fold (p<0.01) and 2.7 fold (p<0.001) increase ofcell entry into S-phase in NIH3T3 and PC3 cells in cell cycle analysis(FIG. 27C). Colony formation analyses indicate that expression ofPTEN-NOLC1 produced 2.2 fold (p<0.001) higher numbers of colonies fromsingle cell suspension for NIH3T3 cells than the un-induced controls and2.7 fold (p<0.01) more colonies for PC3 cells when they were induced toexpress PTEN-NOLC1-FLAG (FIG. 27D).

To investigate the subcellular localization of PTEN-NOLC1, NIH3T3 cellswere transformed with pCDNA4-PTEN-NOLC1-FLAG/pCDNA6 were induced withtetracycline to express PTEN-NOLC1-FLAG. As shown in FIG. 27A, mostPTEN-NOLC1-FLAG was localized in the nucleus of the cells. This iscontrary to cytoplasmic localization of PTEN. PTEN-NOLC1-FLAG was alsodetected in purified nucleus fraction. Without being bound to aparticular theory, these results indicate that fusion formation withNOLC1 alters the subcellular localization of PTEN-NOLC1 from cytoplasmto nucleus.

8. EXAMPLE 3: THERAPEUTIC TARGETING AT FUSION TRANSCRIPT CONTAININGCHIMERA PROTEIN MAN2A1-FER 8.1. Results

MAN2A1-FER likely produces activated FER kinase. MAN2A1-FER was presentin prostate cancer, hepatocellular carcinoma and Glioblastomamultiforme. MAN2A1 is a Golgi enzyme required for conversion of highmannose to complex type structure of N-glycan for mature glycosylationof a membrane protein^(1, 2). Little is known about its relation withhuman malignancies. On the other hand, FER, a tyrosine kinase, is awell-documented oncogene^(3, 4). Several studies showed that FERactivate androgen receptor (AR) by phosphorylating Tyr223 in AR⁵, and isessential for NFκB activation of EGFR⁶. Some studies indicate that FERis an essential component of stem cell tyrosine kinase 1 (STK1)⁶ andmast cell growth factor receptor (kit)^(7, 8) signaling. Over-expressionof FER is associated with poor clinical outcomes of breast cancer⁹,renal cell carcinoma^(10, 11), non-small cell lung cancer^(12, 13) andhepatocellular carcinoma¹⁴. The N-termini of many tyrosine proteinkinases serve to constrain the kinase activity and are regulated byother molecules. Domains of some N-termini bind and select specifictargets for the kinases. Removal of the N-terminus from a protein kinasemay produce constitutively activated kinase activity that may alter thesignaling pathways and generates uninhibited cell growth. The bestanalogy to MAN2A1-FER is BCR-Abl. When c-Abl is intact, its kinaseactivity is constrained. Removal of SH3 domain in c-Abl in the BCR-Ablfusion protein converts the mutant Abl tyrosine kinase into an oncogenethat plays key role in developing acute lymphoblastic leukemia andchronic myelogenous leukemia. Wild type FER with intact SH2 domain isinactive in kinase activity when assayed in cell free system. In thefusion gene MAN2A1-FER, the N-terminus of FER suffers a loss of SH2 andFHC domain (FIG. 14). These domains were replaced with glycosidehydrolase and α-mannosidase middle domain from MAN2A1. As a result, thekinase activity may be activated and substrate targets of FER tyrosinekinase may be altered.

MAN2A1-FER Expression Accelerates Cell Cycle Entry into S Phase andIncreased Tyrosine Phosphorylation of EGFR in the Absence of EGFRLigand.

To investigate whether MAN2A1-FER chimera protein is expressed inprostate cancer samples that contain MAN2A1-FER transcript, proteinextracts from 5 prostate cancer samples positive for MAN2A1-FER RNA wereanalyzed using antibodies specific for MAN2A1 or FER. These resultsshowed that the samples expressed a 115 Kd protein recognized by bothMAN2A1 and FER antibodies (FIG. 22). This protein is not detected inprostate cancer samples that are negative for MAN2A1-FER transcript.

When MAN2A1-FER was forced to express in RWPE1 cells, a non-transformedprostate epithelial cell line, it increase the proportion of cells in Sphase by 4.6-5 fold (p<0.001). MAN2A1-FER was determined to beco-localized with Golgi protein in both immunofluorescence and sucrosegradient analysis, supporting the notion that MAN2A1-FER is primarilylocated in Golgi apparatus. Interestingly, expression of MAN2A1-FERincreased tyrosine phosphorylation of EGFR in RWPE1 cells in the absenceof EGFR ligand, suggesting that MAN2A1-FER may ectopically phosphorylatethe EGFR extracellular domain. Thus, MAN2A1-FER may function as atransforming oncogene and possess intrinsic tyrosine kinase activityderived from its FER kinase domain. Not to be limited to any particulartheory, the kinase domain of MAN2A1-FER may be the driver of itsoncogenic activity through ectopic phosphorylation of transmembraneproteins such as EGFR.

Therapeutic Targeting at MAN2A1-FER Results in Specific Cell DeathProstate Cancer Cells Expressing MAN2A1-FER.

Based on the analyses above, we reason that the altered subcellularlocation and substrate specificity of FER kinase will create oncogenicactivity of MAN2A1-FER. A large part of this oncogenic activity resultsfrom ectopic phosphorylation and activation of EGFR and its down-streamsignaling pathways. Thus, we can intervene and disrupt the oncogenicpathways of MAN2A1-FER using 2 different approaches. The first approachis inhibiting the kinase activity of MAN2A1-FER by targeting MAN2A1-FERproteins using small molecules that can inhibit tyrosine kinase. Severalsmall molecules specific for FER such as diaminopyrimidine TAE684, andpyrazologyrididines WZ-4-49-8 and WZ-4-49-10, generic ALK/FER inhibitorcrisotinib are available. Among these compound inhibitors, Crisotinibhas been approved by FDA to treat advanced and metastatic non-small celllung cancer positive for EML4-ALK, another tyrosine kinase fusionprotein. The drug has been shown to be able to shrink tumor mass by atleast 30% in most patients.

To investigate whether Crisotinib is also effective against MAN2A1-FERpositive cancer cells, we transformed human prostate cancer cell linePC3 with pCDNA4-MAN2A1-FER-FLAG/pCDNA6 to express MAN2A1-FER fusionprotein. These cells were treated with low dosage of Crisotinib for 24hours. As shown in FIG. 22, the treatment resulted in 31% cell death inMAN2A1-FER expressing cells, while it hardly killed the same type ofcancer cells that do not express this fusion protein. A dosage effectanalysis showed that expression of MAN2A1-FER lowers the cancer killingEC₅₀ by at least 2 magnitudes (˜100 fold). Thus, it is reasonable totreat MAN2A1-FER positive prostate cancer with Crisotinib at a dosagethat is not harmful to normal human cells.

The second approach is to target EGFR activation by EGFR inhibitors.These include erlotinib, cetuximab, bevacizumab, canertinib andbortezomib. Many of these drugs were FDA approved and is widely used ina variety of human solid tumors. To interrogate the effectiveness ofEGFR activation interruption in treating prostate cancer, we treatedMAN2A1-FER transformed PC3 cells with canertinib. As shown in FIG. 23,the treatment also produced 34% cell death of cells expressingMAN2A1-FER. In contrast, the effect on cells not expressing MAN2A1-FER(Tet−) was minimal: The cell death level is similar to those untreatedcontrols. These results suggest EGFR activation is one of the criticalpathways for MAN2A1-FER oncogenic activity. Interesting, when we triedto intercept the down-streaming signaling molecule of EGFR, MEK, usingan experimental drug AZD6244, the differential killing effect waslargely moderated and vanished (data not shown). It suggests that othersignaling pathways for EGFR may bypass MEK signaling.

8.2. References

-   1. Moremen K W, Robbins P W: Isolation, characterization, and    expression of cDNAs encoding murine alpha-mannosidase II, a Golgi    enzyme that controls conversion of high mannose to complex    N-glycans, J Cell Biol 1991, 115:1521-1534-   2. Misago M, Liao Y F, Kudo S, Eto S, Mattei M G, Moremen K W,    Fukuda M N: Molecular cloning and expression of cDNAs encoding human    alpha-mannosidase II and a previously unrecognized alpha-mannosidase    IIx isozyme, Proc Natl Acad Sci USA 1995, 92:11766-11770-   3. Hao Q L, Heisterkamp N, Groffen J: Isolation and sequence    analysis of a novel human tyrosine kinase gene, Mol Cell Biol 1989,    9:1587-1593-   4. Krolewski J J, Lee R, Eddy R, Shows T B, Dalla-Favera R:    Identification and chromosomal mapping of new human tyrosine kinase    genes, Oncogene 1990, 5:277-282-   5. Rocha J, Zouanat F Z, Zoubeidi A, Hamel L, Benidir T, Scarlata E,    Brimo F, Aprikian A, Chevalier S: The Fer tyrosine kinase acts as a    downstream interleukin-6 effector of androgen receptor activation in    prostate cancer, Mol Cell Endocrinol 381:140-149-   6. Guo C, Stark G R: FER tyrosine kinase (FER) overexpression    mediates resistance to quinacrine through EGF-dependent activation    of NF-kappaB, Proc Natl Acad Sci USA 108:7968-7973-   7. Kwok E, Everingham S, Zhang S, Greer P A, Allingham J S, Craig A    W: FES kinase promotes mast cell recruitment to mammary tumors via    the stem cell factor/KIT receptor signaling axis, Mol Cancer Res    10:881-891-   8. Voisset E, Lopez S, Dubreuil P, De Sepulveda P: The tyrosine    kinase FES is an essential effector of KITD816V proliferation    signal, Blood 2007, 110:2593-2599-   9. Ivanova I A, Vermeulen J F, Ercan C, Houthuijzen J M, Saig F A,    Vlug E J, van der Wall E, van Diest P J, Vooijs M, Derksen P W: FER    kinase promotes breast cancer metastasis by regulating alpha6- and    beta1-integrin-dependent cell adhesion and anoikis resistance,    Oncogene 32:5582-5592-   10. Miyata Y, Kanda S, Sakai H, Greer P A: Feline sarcoma-related    protein expression correlates with malignant aggressiveness and poor    prognosis in renal cell carcinoma, Cancer Sci 104:681-686-   11. Wei C, Wu S, Li X, Wang Y, Ren R, Lai Y, Ye J: High expression    of FER tyrosine kinase predicts poor prognosis in clear cell renal    cell carcinoma, Oncol Lett 5:473-478-   12. Ahn J, Truesdell P, Meens J, Kadish C, Yang X, Boag A H, Craig A    W: Fer protein-tyrosine kinase promotes lung adenocarcinoma cell    invasion and tumor metastasis, Mol Cancer Res 11:952-963-   13. Kawakami M, Morita S, Sunohara M, Amano Y, Ishikawa R, Watanabe    K, Hamano E, Ohishi N, Nakajima J, Yatomi Y, Nagase T, Fukayama M,    Takai D: FER overexpression is associated with poor postoperative    prognosis and cancer-cell survival in non-small cell lung cancer,    Int J Clin Exp Pathol 6:598-612-   14. Li H, Ren Z, Kang X, Zhang L, Li X, Wang Y, Xue T, Shen Y, Liu    Y: Identification of tyrosine-phosphorylated proteins associated    with metastasis and functional analysis of FER in human    hepatocellular carcinoma cells, BMC Cancer 2009, 9:366-   15. Zha S, Ferdinandusse S, Denis S, Wanders R J, Ewing C M, Luo J,    De Marzo A M, Isaacs W B: Alpha-methylacyl-CoA racemase as an    androgen-independent growth modifier in prostate cancer, Cancer Res    2003, 63:7365-7376-   16. Krastev D B, Slabicki M, Paszkowski-Rogacz M, Hubner N C,    Junqueira M, Shevchenko A, Mann M, Neugebauer K M, Buchholz F: A    systematic RNAi synthetic interaction screen reveals a link between    p53 and snoRNP assembly, Nature cell biology 2011, 13:809-818

9. EXAMPLE 4. ELIMINATION OF CANCER CELLS POSITIVE FOR FUSIONTRANSCRIPTS THROUGH GENOME EDITING

Recent advances in genome editing using ZFN and CAS9 has made itpossible to target a specific cancer genome sequence that is not presentin normal cells. The mechanism of formation of fusion transcript ischromosome rearrangement. As a result, breakpoints in the chromosome arereadily identified in a cancer genome. Normal cells do not have similarchromosome rearrangements, and are thus negative for the breakpoint.Targeting a specific breakpoint in the prostate cancer genome willlikely generate an effective treatment for prostate cancer. Since thegenomic breakpoint of CCNH-C5ORF30 and TMEM135-CCDC67 has beenidentified, genome editing technology targeting at the breakpoint ofCCNH-C5orf30 or TMEM135-CCDC67 can be used to kill cancer cells.

As shown in FIG. 15, genome recombination in prostate cancer case 3Tproduced a breakpoint in chromosome 5 that connect intron 6 of CCNH withintron 1 of C5orf30. The resulting breaking point is unique in prostatecancer case 3T. The breakpoint is positive in most prostate cancertissues but negative for normal tissues from this patient. A guide RNA(gRNA) of 23 bp including protospacer adjacent motif (PAM) sequence isdesigned specific for the breakpoint region. The DNA sequencecorresponding to this target sequence is artificially ligated intovector containing the remainder of gRNA and CAS9. This sequence isrecombined and packaged into recombinant virus (Adenovirus orlenti-virus). A promoterless Herpes Simplex Virus Type 1 (HSV-1)thymidine kinase is constructed into a shuttle vector for adenovirusalong with splice tag sequence from intron/exon juncture of CCNH exon 7.A 500 bp sequence surrounding the CCNH-C5orf30 breakpoint from each sideis also ligated into the shuttle vector in order to produce efficienthomologous recombination to complete the donor DNA construction. Thevector is recombined and packaged into AdEasy to generate recombinantviruses. These viruses are administered to patients or animals that havecancer positive for CCNH-C5orf30 fusion transcript. This leads toinsertion of donor DNA into the target site (fusion breakpoint). SinceHSV-1 TK in recombinant virus is promoterless, no transcription willoccur if HSV-1 TK cDNA does not integrate into a transcription activegenome. However, transcription of HSV-1 TK is active if HSV-1 TK isintegrated into the target site of CCNH-C5orf30, since this transcriptis readily detectable in the prostate cancer sample of this patient.When patient 3T takes ganciclovir or its oral homologue valganciclovir,the homologue is readily converted to triphosphate guanine analogue byHSV-1 TK and incorporated into the genomes of cancer cells. This leadsto stoppage of DNA elongation in cells that are positive forCCNH-C5orf30. Since mammalian TK does not phosphorylate ganciclovir,ganciclovir is not converted to active (triphosphate) form in cells thatare negative for HSV-1 TK protein. Thus, the impact of ganciclovir onnormal cells is minimized.

The technique described above was applied to cells having theTMEM135-CCDC67 breakpoint. Since none of the fusion genes we identifiedso far was present in prostate cancer cell lines, we created aTMEM135-CCDC67 genome breakpoint that is identical to the prostatecancer sample we analyzed. The expression of the TMEM135-CCDC67breakpoint was driven by a CMV promoter. Subsequently, we constructed adonor DNA that encompassed HSV-1 TK and the splicing sites of TMEM135exon 14. When we co-transfected this donor DNA with a vector thatexpresses gRNA targeting at the TMEM135-CCDC67 breakpoint into PC3 cellscontaining this genome breakpoint, integration of TK into the genome wasidentified (FIG. 28A). In contrast, when we transfected the same pairsof DNA into cells that do not contain the breakpoint, no integration ofTK was found (data not shown). Treatment of PC3 cells withoutTMEM135-CCDC67 breakpoint has minimal cell death, while the sametreatment of PC3 cells containing the breakpoint with ganciclovirresulted in 8 fold increase of cell death (FIG. 28B). This is remarkablein considering only 5-10% transfection efficiency using conventionalliposome method. Without being limited to a particular theory, thesedata suggest that almost all the cells receiving the DNA died whentreated with ganciclovir, if they contain the breakpoint. In light ofthis promising result, both TMEM135-CCDC67-TK cassette andNicKase-gRNATMEM135-CCDC67-BrkPt DNA are now in the process of packaginginto Adenovirus. We will infect the recombinant virus into these cellsin the future experiments. This will dramatically improve the deliveryefficiency in the subsequent animal study and probably human.

10. EXAMPLE 5: NOVEL FUSION TRANSCRIPTS ASSOCIATE WITH PROGRESSIVEPROSTATE CANCER

The analysis of an additional 68 prostate cancer samples bytranscriptome sequencing leads to the discovery of 5 additional novelfusion transcripts present in prostate cancer. It is noted thatsignificant number of prostate cancers contained no fusion transcriptsin RNA sequencing. Even though extensive transcriptome sequencings wereperformed on 30 prostate cancer samples that prove non-recurrent forextended period of time, no viable fusion transcripts were identified inthese samples using fusion catcher software. These 5 fusion transcriptswere validated through Sanger sequencing of the RT-PCR products (FIG.16). The following primers were used: ACPP-SEC13:5′-TCCCATTGACACCTTTCCCAC (SEQ ID NO: 30)/5′-TGAGGCTTCCAGGTACAACAG (SEQID NO: 31); CLTC-ETV1: 5′-GCCCAGTTGCAGAAAGGAATG (SEQ ID NO:32)/5′-CTTGATTTTCAGTGGCAGGCC (SEQ ID NO: 33); DOCK7-OLR1:5′-GACTACGTCTCATGCCTTTCC (SEQ ID NO: 34)/5′-TTCTCATCAGGCTGGTCCTTC (SEQID NO: 35); PCMTD1-SNTG: 5′-GATGTGGTGGAATATGCCAAGG (SEQ ID NO:36)/5′-AAATCCATGTGCTGTGGCACC (SEQ ID NO: 37); and ZMPSTE24-ZMYM4:5′-CGCAATGAGGAAGAAGGGAAC (SEQ ID NO: 38)/5′-CATAAATCTGGAATAGGGCTCAG (SEQID NO: 39).

10.1. Results

ZMPSTE24-ZMYM4 Fusion Genes.

This fusion transcript was discovered in a prostate cancer sample from apatient who experienced prostate cancer recurrence 1.8 month afterradical prostatectomy. The patient's pelvic lymph nodes were positivefor metastatic prostate cancer, while his primary cancer sample wasgraded with Gleason 7. In addition to ZMPSTE24-ZMYM4, his prostatecancer sample was also positive for CCNH-c5orf30. ZMPSTE24 is azinc-metalloproteinase involved in post-translational proteolyticcleavage that coverts farnesylated prelamin A to form mature lamin A.Mutation of this protein is associated with mandibuloacral dysplasia¹.It was suggested that ZMPSTE24 may be a mediator promoting invasiveprostate cancer². ZMYM4 is an anti-apoptotic gene whose function domainis located in the 3′ untranslated region. Expression of ZMYM4 3′ UTR hasbeen shown to resist cell death induced by interferon γ throughinhibition of AUF1 activity³. The fusion formation between ZMPSTE24 andZMYM4 produces a truncation of 159 amino acids from the C-terminus ofZMPSTE24 and 1315 amino acids from the N-terminus of ZMYM4. Motifanalysis suggests that ZMPSTE24-ZMYM4 fusion will delete about 50% ofthe peptidase domain from ZMPSTE24 and remove all zinc fingers fromZMYM4, but leave ZUF3504 (domain of unknown function) and apoptosisinhibitor domain intact (FIG. 17). Thus, ZMPSTE24-ZMYM4 fusion mayprovide cancer cells an important tool to resist program cell death.

CLTC-ETV1 Fusion Genes.

CLTC-ETV1 was discovered in a prostate cancer sample that has Gleason'sgrade of 7. The patient experienced prostate cancer recurrence 22 monthsafter radical prostatectomy, and had been rapidly progressing. Inaddition to CLTC-ETV1, the prostate cancer sample was also positive forTRMT11-GRIK2 fusion. CLTC is a major protein component of coatedvesicles and coated pits, and is universally expressed. Its presence isessential for cell shape formation and cell motility. ETV1 is atranscription factor that was shown to over-express in prostate cancer.ETV1 had been shown to partner at least 12 different head genes inprostate cancer and Ewing's sarcoma^(4,5). However, most of thesefusions do not produce a functional transcription factor from ETV1 dueto frameshift in the fusion or few amino acids left after the fusion. Incontrary, CLTC-ETV1 fusion preserves a largely intact transcriptiondomain in ETV1, and probably represents the first example of potentialfunctional ETV1 fusion in prostate cancer. CLTC-ETV1 fusion deletes 3clathrin domains from CLTC (FIG. 18). This may impair the function ofCLTC for coated pit formation. ETV1 has been shown to be oncogenic inseveral organ systems⁶⁻⁸. The regulatory domain is located in theN-terminus. The regulatory domain contains MAPK phosphorylation site aswell as ubiquitination site by COP1^(9,10). Truncation in the N-terminusof ETV1 eliminates all these regulatory elements from ETV1. Thus, theprotein level CLTC-ETV1 may be increased due to less degradation andactivity of ETV1 may become constitutive due to the lack of regulatoryconstraint in the fusion protein. Since ETV1 has been shown tooverexpress in many prostate cancers, CLTC-ETV1 fusion might be theunderlying mechanism.

ACPP-SEC13 Fusion Genes.

The ACPP-SEC13 fusion transcript was discovered in a prostate cancersample from patients who experienced recurrence but also had a slow riseof PSA with doubling time more than 20 months. The Gleason's grade is 7.The pathological examination reveals invasion into seminal vesicle byprostate cancer cells. ACPP is prostate specific acid phosphatase and isabundantly expressed in prostate acinar cells, while SEC13 belongs tothe family of WD-repeat proteins, and is required for vesicle biogenesisfrom endoplasmic reticulum¹¹. Recent studies suggest that SEC13 is asubunit of GATOR2, an octomeric GTPase activating protein. Inhibition ofSEC13 suppresses mTOR activation¹². In ACPP-SEC13 fusion, only theN-terminus 72 amino acids of ACPP is preserved, and over 2/3 of thephosphatase domain is truncated, while SEC13 loses 196 amino acids fromits N-terminus and has 3 WD-repeat domains deleted (FIG. 19). Due to thelarge truncation of critical domains in both proteins, it is expectedthat ACPP-SEC13 contains neither phosphatase nor GTPase-activationactivity. Such loss of function may lead to hyperactivity of mTOR andmay make it insensitive to amino acid deprivation. A potential targetedtreatment for patients positive for ACPP-SEC13 might be using mTORinhibitor since cancer cells may become hypersensitive to mTORinhibitors when SEC13 is not functional.

DOCK7-OLR1 Fusion Genes.

DOCK7-OLR1 fusion transcript was discovered in a prostate cancer samplefrom a patient who experienced recurrent prostate cancer 30.5 monthsafter the radical prostatectomy. However, the rise of PSA appeared rapidwith PSADT less than 3 months. The prostate cancer Gleason's grade was7, and there was no invasion into seminal vesicle or other adjacentorgans at the time of surgery. The surgical margin was negative. Itclearly suggests that some prostate cancer cells had escaped the primarylocation before the surgery. DOCK7 is a guanine nucleotide exchangefactor involving in migration and cell polarization^(13,14), while OLR1is a low density lipoprotein receptor that belongs to the C-type lectinsuperfamily. OLR1 binds, internalizes and degrades oxidized low-densitylipoprotein¹⁵. Unlike the above 3 fusion transcripts, DOCK7-OLR1 doesnot produce a chimera protein. Instead, separate translation of DOCK7and OLR1 occurs from the fusion transcript. The fusion deleted asignificant portion of cytokinesis domain of DOCK7 such that motilityregulation by DOCK7 might be compromised. However, the fusion transcriptwill produce an intact OLR1 protein (FIG. 20). OLR1 was implicated inFas-mediated apoptosis. The functional significance of its expressionunder the control of DOCK7 promoter is to be investigated.

PCMTD1-SNTG1 Fusion Genes.

PCMTD1-SNTG1 fusion transcript was discovered in a prostate cancersample from a patient who experienced recurrent prostate cancer 5.5months after the radical prostatectomy. The rise of PSA was rapid withPSADT less than 3 months. The Gleason's grade is 9. Seminal vesicleinvasion was identified in the prostatectomy sample. The prostate cancersample is also positive for SLC45A2-AMACR and LRRC59-FLJ60017. PCMTD1 isDaspartate methyltransferase domain containing protein. The function ofPCMTD1 has not been studied. SNTG1 is a member of the syntrophin family.SNTG1 belongs to peripheral membrane protein. Recent study suggests thatSNTG1 may regulate diacylglycerol kinase zeta subcellular localizationand regulates the termination of diacylglycerol signaling. Similar toDOCK7-OLR1 fusion, PCMTD1-SNTG1 fusion does not produce a chimeraprotein. PCMTD1-SNTG1 fusion produces a truncated PCMTD1. The truncationremoves half of the methyl-transferase domain of PCMTD1. However, SNTG1is intact (FIG. 21). Since diacylglycerol kinase weakens protein kinaseC activity by depleting the availability of diacylglycerol, higher levelof SNTG1 might enhance PKC signaling If PCMDT1-SNTG1 fusion drives upthe expression of SNTG1. Alternatively, impairing the function of PCMTD1may have impact on cell metabolism and cell growth that are yet to bedelineated.

10.2. References

-   1. Agarwal, A. K., Fryns, J. P., Auchus, R. J., and Garg, A. (2003)    Zinc metalloproteinase, ZMPSTE24, is mutated in mandibuloacral    dysplasia. Human molecular genetics 12(16), 1995-2001.-   2. Parr-Sturgess, C. A., Tinker, C. L., Hart, C. A., Brown, M. D.,    Clarke, N. W., and Parkin, E. T. Copper modulates zinc    metalloproteinase-dependent ectodomain shedding of key signaling and    adhesion proteins and promotes the invasion of prostate cancer    epithelial cells. Mol Cancer Res 10(10), 1282-1293.-   3. Shchors, K., Yehiely, F., Kular, R. K., Kotlo, K. U., Brewer, G.,    and Deiss, L. P. (2002) Cell death inhibiting RNA (CDIR) derived    from a 3′-untranslated region binds AUF1 and heat shock protein. 27.    The Journal of biological chemistry 277(49), 47061-47072.-   4. Clark, J. P., and Cooper, C. S. (2009) ETS gene fusions in    prostate cancer. Nat Rev Urol 6(8), 429-439.-   5. Jeon, I. S., Davis, J. N., Braun, B. S., Sublett, J. E.,    Roussel, M. F., Denny, C. T., and Shapiro, D. N. (1995) A variant    Ewing's sarcoma translocation (7; 22) fuses the EWS gene to the ETS    gene ETV1. Oncogene 10(6), 1229-1234.-   6. Carver, B. S., Tran, J., Chen, Z., Carracedo-Perez, A., Alimonti,    A., Nardella, C., Gopalan, A., Scardino, P. T., Cordon-Cardo, C.,    Gerald, W., and Pandolfi, P. P. (2009) ETS rearrangements and    prostate cancer initiation. Nature 457(7231), E1; discussion E2-3.-   7. Chi, P., Chen, Y., Zhang, L., Guo, X., Wongvipat, J., Shamu, T,    Fletcher, J. A., Dewell, S., Maki, R. G., Zheng, D., Antonescu, C.    R., Allis, C. D., and Sawyers, C. L. ETV1 is a lineage survival    factor that cooperates with KIT in gastrointestinal stromal tumours.    Nature 467(7317), 849-853.-   8. Jane-Valbuena, J., Widlund, H. R., Perner, S., Johnson, L. A.,    Dibner, A. C., Lin, W. M., Baker, A. C., Nazarian, R. M.,    Vijayendran, K. G., Sellers, W. R., Hahn, W. C., Duncan, L. M.,    Rubin, M. A., Fisher, D. E., and Garraway, L. A. An oncogenic role    for ETV1 in melanoma. Cancer research 70(5), 2075-2084.-   9. Vitari, A. C., Leong, K. G., Newton, K., Yee, C., O'Rourke, K.,    Liu, J., Phu, L., Vij, R., Ferrando, R., Couto, S. S., Mohan, S.,    Pandita, A., Hongo, J. A., Arnott, D., Wertz, I. E., Gao, W. Q.,    French, D.-   10. M., and Dixit, V. M. COP1 is a tumour suppressor that causes    degradation of ETS transcriptionfactors. Nature 474(7351), 403-406-   11. Willardsen, M., Hutcheson, D. A., Moore, K. B., and    Vetter, M. L. The ETS transcription factor Etv1 mediates FGF    signaling to initiate proneural gene expression during Xenopus    laevis retinal development. Mechanisms of development 131, 57-67-   12. Enninga, J., Levay, A., and Fontoura, B. M. (2003) Sec13    shuttles between the nucleus and the cytoplasm and stably interacts    with Nup96 at the nuclear pore complex. Molecular and cellular    biology 23(20), 7271-7284.-   13. Bar-Peled, L., Chantranupong, L., Cherniack, A. D., Chen, W. W.,    Ottina, K. A., Grabiner, B. C., Spear, E. D., Carter, S. L.,    Meyerson, M., and Sabatini, D. M. A Tumor suppressor complex with    GAP activity for the Rag GTPases that signal amino acid sufficiency    to mTORC1. Science (New York, N. Y340(6136), 1100-1106.-   14. Watabe-Uchida, M., John, K. A., Janas, J. A., Newey, S. E., and    Van Aelst, L. (2006) The Rac activator DOCK7 regulates neuronal    polarity through local phosphorylation of stathmin/Op18. Neuron    51(6), 727-739.-   15. Nellist, M., Burgers, P. C., van den Ouweland, A. M., Halley, D.    J., and Luider, T. M. (2005) Phosphorylation and binding partner    analysis of the TSC1-TSC2 complex. Biochemical and Biophysical    Research Communications 333(3), 818-826.

11. EXAMPLE 6: SLC45A2-AMACR FUSION GENES 11.1 Results

The fusion transcript of Solute carrier family 45, member2-alpha-methylacyl-CoA racemase (SLC45A2-AMACR) produces a chimeraprotein with Nterminus 187 amino acids of SLC45A2 and the C-terminus 311amino acids of AMACR. SLC45A2 is a transporter protein known to beoverexpressed in melanoma¹, while AMACR is an enzyme involved inmetabolism of branch fatty acid, and is known for its overexpression inseveral human malignancies. SLC45A2-AMACR replaces 5 transmembrane andcytosolic domains of SLC45A2 with an intact racemase domain from AMACR²,while leaves the extracellular and the N-terminal transmembrane domainsintact (FIG. 24). Most of prostate cancer patients who were positive forSLC45A2-AMACR experienced prostate cancer recurrence within 5 years ofsurgical treatment. Previous studies suggest that AMACR is essential foroptimal growth of prostate cancer cells in vivo. Knocking down of AMACRor treatment of prostate cancer with AMACR inhibitors resulted in deathof cancer cells both in vitro and in vivo³. Formation of SLC45A2-AMACRgenerates ectopic racemase for fatty acid metabolism to support thegrowth of prostate cancer cells.

Transformation of Prostate Epithelial Cells with SLC45A2 AMACR Resultsin Dramatic Cell Growth and Transformation, Possibly Through Activationof SHIP2-Akt Pathway.

To investigate whether SLC45A2-AMACR chimera protein is expressed inprostate cancer samples that contain SLC45A2-AMACR transcript, proteinextracts from 4 prostate cancer samples positive for SLC45A2-AMACR RNAwere analyzed using antibodies specific for MAN2A1 or FER. The resultsshowed that these samples expressed a 50 Kd protein recognized by bothMAN2A1 and FER antibodies (FIG. 25A). This protein was not detected inprostate cancer samples that were negative for SLC45A2-AMACR transcript.When SLC45A2-AMACR was forced to express in RWPE1 cells, anon-transformed prostate epithelial cell line, it increased theproportion of cells in S phase by an average of 8.7 fold (p<0.001). MTTassays showed a 7.5 fold increase of cell proliferation (p<0.001)(FIG.25 E-F). SLC45A2-AMACR was determined to be localized in the plasmamembrane by immunofluorescence staining and membranous fractionationanalyses. This is in contrast to native AMACR, which is locatedprimarily in the mitochondria/cytoplasm. To investigate what are thepotential signaling molecules mediating SLC45A2-AMACR induced cellgrowth and DNA synthesis. Yeast-two hybrid screening of prostate Yeasttwo-Hybrid library using pBD-SLC45A2-AMACR was performed. After 3 roundsof metabolic screening, 15 unique clones that contain SLC45A2-AMACRbinding proteins were identified. One of these clones encodes inositolpolyphosphate phosphatase-like 1 (INPPL1, also called SHIP2). SHIP2 is aSH2 domain containing inositol phosphatase that converts PIP₃(3,4,5) toPIP₂(3,4). In contrast to Pten, which converts PIP₃(3,4,5) to aninactive PIP₂(4,5), PIP₂(3,4) generated by SHIP2 has higher affinitybinding with AKT than PIP₃(3,4,5), and thus hyper-activate AKT pathway.The interaction between SLC45A2 and SHIP2 was validated by both yeastTwo-hybrid co-transfection analysis and co-immunoprecipitation assays inSLC45A2-AMACR expressing cells (FIG. 25G-H). Induction of SLC45A2-AMACRexpression in 2 different clones of RWPE1 cells generated 2.1- and2.3-fold higher level of PIP2(3,4), respectively. These results indicatethat binding of SLC45A2-AMACR and SHIP2 leads to activation of SHIP2phosphatase activity and probably AKT signaling pathway.

Therapeutic Targeting at SLC45A2-AMACR Using Racemase Inhibitor.

To investigate whether targeting SLC45A2-AMACR is a viable approach totreat prostate cancer, we chose 2 approaches: 1) To interceptSLC45A2-AMACR/SHIP2-Akt pathway with small molecules; and 2) to blockthe ectopic racemase activity of SLC45A2-AMACR with ebselen ortrifluoro-ibuprofen. Surprisingly, both SHIP2 and MTOR inhibitors killedPC3 cells effectively, regardless whether they were transformed withSLC45A2-AMACR. Expression of SLC45A2-AMACR only moderately sensitizedPC3 cells to Rapamycin. This is probably due to Pten negative status ofPC3 cells such that Akt pathway is fully activated regardless thepresence of SLC45A2-AMACR. On the other hand, when we applied ebselen,the potent inhibitor of racemase of AMACR, to SLC45A2-AMACR expressingPC3 cells, 5 fold higher sensitivity of cell growth inhibition was foundfor PC3 cells transformed with pCDNA4-SLC45A2-AMACR-FLAG/pCDNA6 over thecontrols. In contrast, non-transformed RWPE1 cells and

NIH3T3 cells that expressed little AMACR was largely insensitive toebselen killing (FIG. 26). The differential sensitivity of normal cellsversus cancer cells to AMACR inhibitors may prove very useful intreating prostate cancer positive for this fusion gene.

11.2. References

-   1. Misago, M., Liao, Y. F., Kudo, S., Eto, S., Mattei, M. G.,    Moremen, K. W., and Fukuda, M. N. (1995) Molecular cloning and    expression of cDNAs encoding human alpha-mannosidase II and a    previously unrecognized alpha-mannosidase IIx isozyme. Proceedings    of the National Academy of Sciences of the United States of America    92(25), 11766-11770.-   2. Krolewski, J. J., Lee, R., Eddy, R., Shows, T. B., and    Dalla-Favera, R. (1990) Identification and chromosomal mapping of    new human tyrosine kinase genes. Oncogene 5(3), 277-282.-   3. Zha, S., Ferdinandusse, S., Denis, S., Wanders, R. J., Ewing, C.    M., Luo, J., De Marzo, A. M., and Isaacs, W. B. (2003)    Alpha-methylacyl-CoA racemase as an androgen-independent growth    modifier in prostate cancer. Cancer research 63(21), 7365-7376.

Various references are cited in this document, which are herebyincorporated by reference in their entireties herein.

What is claimed is:
 1. A method of treating a subject, comprising (i)determining whether a subject is at increased risk of manifestingprogressive prostate cancer comprising determining whether a prostatecancer cell of the subject contains a SLC45A2-AMACR fusion gene; and(ii) where the cell contains the SLC45A2-AMACR fusion gene so that thesubject is at increased risk, performing one or more of cryotherapy,radiation therapy, chemotherapy, hormone therapy, and radicalprostatectomy.
 2. The method of claim 1, wherein the fusion gene isdetected by fluorescence in situ hybridization (FISH) analysis.
 3. Themethod of claim 1, wherein the fusion gene is detected by polymerasechain reaction (PCR).
 4. The method of claim 1, wherein the fusion geneis detected by Western blot analysis.
 5. The method of claim 1, whereinthe subject is determined to be at increased risk of rapid relapse. 6.The method of claim 1, wherein the subject is determined to be atincreased risk of relapse.
 7. The method of claim 1, further comprisingdetermining a nomogram score of the subject.
 8. A method of treating asubject, comprising: (i) determining whether a subject is at increasedrisk of manifesting progressive prostate cancer comprising determiningwhether a prostate cancer cell of the subject contains a SLC45A2-AMACRfusion gene; and (ii) where the cell contains the SLC45A2-AMACR fusiongene so that the subject is at increased risk; (a) administering atherapeutically effective amount of an inhibitor of the SLC45A2-AMACRfusion protein; (b) administering a therapeutically effective amount ofan agent that inhibits the SLC45A2-AMACR fusion protein; (c)administering a therapeutically effective amount of an siRNA targetingthe SLC45A2-AMACR fusion gene contained within the prostate cancer cell;(d) administering a therapeutically effective amount of an anti-canceragent selected from the group consisting of chemotherapeutic agents,radiotherapeutic agents, cytokines, anti-angiogenic agents,apoptosis-inducing agents, and anti-cancer immunotoxins; and/or (e)performing a targeted genome editing procedure on one or more prostatecancer cells within the subject.
 9. The method of claim 8, wherein thefusion gene is detected by fluorescence in situ hybridization (FISH)analysis.
 10. The method of claim 8, wherein the fusion gene is detectedby polymerase chain reaction (PCR).
 11. The method of claim 8, whereinthe fusion gene is detected by Western blot analysis.
 12. The method ofclaim 8, wherein the subject is determined to be at increased risk ofrapid relapse.
 13. The method of claim 8, wherein the subject isdetermined to be at increased risk of relapse.
 14. The method of claim8, wherein a therapeutically effective amount of an inhibitor of theSLC45A2-AMACR fusion protein is administered.
 15. The method of claim14, wherein the inhibitor of the SLC45A2-AMACR fusion protein isselected from the group consisting of ebselen,2-(2,5-dihydroxy-4-methylphenyl)-5-methyl benzene-1,4-diol (DMPMB),2-methylsulfanyl-7,9-dihydro-3H-purine-6,8-dithione (MSDTP),2,5-di(pyrazol-1-yl)benzene-1,4-diol (DPZBD), Rose Bengal, Congo Red,3,5-di(pyridin-4-yl)-1,2,4-thiadiazole (DPTD), ebselen oxide,3,7,12-trihydroxycholestanoyl Coenzyme A (THCA-CoA),N-methylthiocarbamate, trifluoro-ibuprofen and combinations thereof. 16.The method of claim 14, wherein the inhibitor of the SLC45A2-AMACRfusion protein is a racemase inhibitor.
 17. The method of claim 14,wherein the inhibitor of the SLC45A2-AMACR fusion protein is an AMACRinhibitor.
 18. The method of claim 16, wherein the racemase inhibitor isebselen.
 19. The method of claim 16, wherein the method furthercomprises administering a therapeutically effective amount of an AMACRinhibitor.